Comprehensive survey on hierarchical clustering algorithms and the recent developments

Data clustering is a commonly used data processing technique in many fields, which divides objects into different clusters in terms of some similarity measure between data points. Comparing to partitioning clustering methods which give a flat partition of the data, hierarchical clustering methods ca...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	The Artificial intelligence review Jg. 56; H. 8; S. 8219 - 8264
Hauptverfasser:	Ran, Xingcheng, Xi, Yue, Lu, Yonggang, Wang, Xiangwen, Lu, Zhenyu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.08.2023 Springer Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Cluster analysis Clustering Computer Science Data points Data processing Deep learning Hierarchies Partition Production methods Similarity Similarity measures Surveys Divisive Agglomerative Similarity Hierarchical clustering Dissimilarity
ISSN:	0269-2821, 1573-7462
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	Data clustering is a commonly used data processing technique in many fields, which divides objects into different clusters in terms of some similarity measure between data points. Comparing to partitioning clustering methods which give a flat partition of the data, hierarchical clustering methods can give multiple consistent partitions of the data at different levels for the same data without rerunning clustering, it can be used to better analyze the complex structure of the data. There are usually two kinds of hierarchical clustering methods: divisive and agglomerative. For the divisive clustering, the key issue is how to select a cluster for the next splitting procedure according to dissimilarity and how to divide the selected cluster. For agglomerative hierarchical clustering, the key issue is the similarity measure that is used to select the two most similar clusters for the next merge. Although both types of the methods produce the dendrogram of the data as output, the clustering results may be very different depending on the dissimilarity or similarity measure used in the clustering, and different types of methods should be selected according to different types of the data and different application scenarios. So, we have reviewed various hierarchical clustering methods comprehensively, especially the most recently developed methods, in this work. The similarity measure plays a crucial role during hierarchical clustering process, we have reviewed different types of the similarity measure along with the hierarchical clustering. More specifically, different types of hierarchical clustering methods are comprehensively reviewed from six aspects, and their advantages and drawbacks are analyzed. The application of some methods in real life is also discussed. Furthermore, we have also included some recent works in combining deep learning techniques and hierarchical clustering, which is worth serious attention and may improve the hierarchical clustering significantly in the future.
AbstractList	Data clustering is a commonly used data processing technique in many fields, which divides objects into different clusters in terms of some similarity measure between data points. Comparing to partitioning clustering methods which give a flat partition of the data, hierarchical clustering methods can give multiple consistent partitions of the data at different levels for the same data without rerunning clustering, it can be used to better analyze the complex structure of the data. There are usually two kinds of hierarchical clustering methods: divisive and agglomerative. For the divisive clustering, the key issue is how to select a cluster for the next splitting procedure according to dissimilarity and how to divide the selected cluster. For agglomerative hierarchical clustering, the key issue is the similarity measure that is used to select the two most similar clusters for the next merge. Although both types of the methods produce the dendrogram of the data as output, the clustering results may be very different depending on the dissimilarity or similarity measure used in the clustering, and different types of methods should be selected according to different types of the data and different application scenarios. So, we have reviewed various hierarchical clustering methods comprehensively, especially the most recently developed methods, in this work. The similarity measure plays a crucial role during hierarchical clustering process, we have reviewed different types of the similarity measure along with the hierarchical clustering. More specifically, different types of hierarchical clustering methods are comprehensively reviewed from six aspects, and their advantages and drawbacks are analyzed. The application of some methods in real life is also discussed. Furthermore, we have also included some recent works in combining deep learning techniques and hierarchical clustering, which is worth serious attention and may improve the hierarchical clustering significantly in the future.
Audience	Academic
Author	Xi, Yue Lu, Yonggang Wang, Xiangwen Ran, Xingcheng Lu, Zhenyu
Author_xml	– sequence: 1 givenname: Xingcheng orcidid: 0000-0003-4097-0709 surname: Ran fullname: Ran, Xingcheng organization: School of Information Science and Engineering, Lanzhou University, Center of Information Technology, Hexi University – sequence: 2 givenname: Yue surname: Xi fullname: Xi, Yue organization: School of Information Science and Engineering, Lanzhou University – sequence: 3 givenname: Yonggang orcidid: 0000-0001-8926-2039 surname: Lu fullname: Lu, Yonggang email: ylu@lzu.edu.cn organization: School of Information Science and Engineering, Lanzhou University – sequence: 4 givenname: Xiangwen surname: Wang fullname: Wang, Xiangwen organization: School of Information Science and Engineering, Lanzhou University – sequence: 5 givenname: Zhenyu surname: Lu fullname: Lu, Zhenyu organization: School of Information Science and Engineering, Lanzhou University
BookMark	eNp9kE1r3DAQhkXZQDZJ_0BOgp6d6sOS7eOytElhoZe2V6FI47UWW3IleWH_fbR1odBD0GHEMM-8zHOHNj54QOiRkidKSPM5UVJLVhHGKkq4lBX_gLZUNLxqSn-DtoTJrmIto7foLqUTIUSwmm_Rr32Y5ggD-OTOgNMSz3DBwePBQdTRDM7oEZtxSRmi80esx2OILg9TwtpbnAfAEQz4jC2cYQzzVP7pAd30ekzw8W-9Rz-_fvmxf6kO35-_7XeHynDR5kr0ltaEWdsRY2stjdBUCkZb2Xc90VZY6IF2DXAKdScFf9Xcku7VMm4kB8Lv0ad17xzD7wVSVqewRF8iVTm26xpZ102ZelqnjnoE5XwfctSmPAuTM8Vk70p_14iS0bT8CrAVMDGkFKFXc3STjhdFiboKV6twVYSrP8IVL1D7H2Rc1tkFX9Lc-D7KVzTNV8kQ_53xDvUGyHiYKw
CitedBy_id	crossref_primary_10_1002_anie_202410881 crossref_primary_10_1016_j_chemosphere_2024_142597 crossref_primary_10_1109_ACCESS_2023_3327640 crossref_primary_10_1007_s11069_025_07663_9 crossref_primary_10_1007_s10618_025_01098_3 crossref_primary_10_1109_TP_2025_3527461 crossref_primary_10_1016_j_bdr_2023_100413 crossref_primary_10_1093_bib_bbaf292 crossref_primary_10_1016_j_socnet_2024_07_003 crossref_primary_10_1088_1742_6596_3078_1_012050 crossref_primary_10_1016_j_sasc_2025_200221 crossref_primary_10_1371_journal_pone_0321847 crossref_primary_10_3390_a18080532 crossref_primary_10_3390_a17120551 crossref_primary_10_1080_15623599_2024_2303884 crossref_primary_10_3390_ijgi14090331 crossref_primary_10_1142_S0219519425400639 crossref_primary_10_24857_rgsa_v19n2_067 crossref_primary_10_3390_w17152242 crossref_primary_10_1038_s40494_025_01967_6 crossref_primary_10_3390_ma18102307 crossref_primary_10_1007_s10115_024_02272_7 crossref_primary_10_1177_03611981241299744 crossref_primary_10_1109_ACCESS_2025_3588502 crossref_primary_10_1007_s40747_024_01460_w crossref_primary_10_1016_j_aei_2025_103182 crossref_primary_10_1016_j_inffus_2025_103434 crossref_primary_10_1016_j_ijar_2025_109422 crossref_primary_10_3390_jcm14165802 crossref_primary_10_1007_s10518_025_02190_1 crossref_primary_10_1016_j_engappai_2025_111042 crossref_primary_10_3390_machines13070559 crossref_primary_10_3390_app15010043 crossref_primary_10_1016_j_ins_2025_122414 crossref_primary_10_1016_j_tws_2024_112274 crossref_primary_10_3390_su16166887 crossref_primary_10_3390_informatics12020038 crossref_primary_10_3390_math13152414 crossref_primary_10_60084_jeml_v3i1_308 crossref_primary_10_3390_logistics9030108 crossref_primary_10_1109_LSP_2025_3582536 crossref_primary_10_1109_OJCSYS_2025_3585427 crossref_primary_10_3390_e26070579 crossref_primary_10_1108_MD_10_2022_1336 crossref_primary_10_1016_j_eswa_2023_122748 crossref_primary_10_1080_23311886_2025_2467226 crossref_primary_10_1108_EC_09_2024_0898 crossref_primary_10_1007_s00217_024_04645_2 crossref_primary_10_1038_s41598_024_59359_y crossref_primary_10_1016_j_eswa_2025_128883 crossref_primary_10_1002_ange_202410881 crossref_primary_10_3390_app15063020 crossref_primary_10_1016_j_scitotenv_2024_170188 crossref_primary_10_3390_s25123609 crossref_primary_10_1007_s00216_023_04991_2 crossref_primary_10_1002_anse_202500052 crossref_primary_10_1016_j_diamond_2025_112352 crossref_primary_10_1007_s12065_025_01018_w crossref_primary_10_1016_j_engappai_2024_109249 crossref_primary_10_1007_s10973_025_14200_0 crossref_primary_10_1109_TCE_2025_3541440 crossref_primary_10_1016_j_cities_2025_106300 crossref_primary_10_1016_j_inffus_2024_102736 crossref_primary_10_1016_j_forsciint_2024_112236 crossref_primary_10_1016_j_swevo_2025_101863 crossref_primary_10_1002_adfm_202508438 crossref_primary_10_1016_j_cej_2025_162154 crossref_primary_10_1007_s42044_025_00294_0 crossref_primary_10_1016_j_cis_2025_103671 crossref_primary_10_1016_j_fub_2025_100093 crossref_primary_10_1007_s10586_024_04664_4 crossref_primary_10_35848_1347_4065_addb54 crossref_primary_10_3390_app13084754 crossref_primary_10_1016_j_tourman_2025_105209 crossref_primary_10_1016_j_jfca_2025_107821 crossref_primary_10_61186_jgeri_2_2_79 crossref_primary_10_1038_s41598_025_13670_4 crossref_primary_10_1088_1742_6596_2706_1_012001 crossref_primary_10_1016_j_aei_2024_102799 crossref_primary_10_1080_87559129_2025_2499645 crossref_primary_10_3390_biology14030283 crossref_primary_10_1016_j_cag_2025_104233 crossref_primary_10_1016_j_cities_2025_106295 crossref_primary_10_1007_s00357_025_09516_3 crossref_primary_10_3390_en18102465 crossref_primary_10_1007_s10115_024_02160_0 crossref_primary_10_1093_nar_gkae099 crossref_primary_10_1016_j_talanta_2024_125845 crossref_primary_10_1080_23307706_2025_2492648 crossref_primary_10_3390_microorganisms12122521 crossref_primary_10_1016_j_engappai_2024_108215 crossref_primary_10_3390_soc15030065 crossref_primary_10_1039_D4CS01293C crossref_primary_10_3390_app14010380 crossref_primary_10_1016_j_asoc_2025_112789 crossref_primary_10_3390_app15063050 crossref_primary_10_1016_j_sbsr_2024_100697 crossref_primary_10_1108_EC_06_2024_0542 crossref_primary_10_1038_s41598_024_72504_x crossref_primary_10_1016_j_foodchem_2025_145581 crossref_primary_10_1007_s10489_024_05913_0 crossref_primary_10_1007_s11227_024_06885_1 crossref_primary_10_3390_pr11113217 crossref_primary_10_3390_s25010073 crossref_primary_10_1016_j_rineng_2025_106498 crossref_primary_10_1007_s11042_024_19545_6 crossref_primary_10_1109_TMI_2024_3520602 crossref_primary_10_1016_j_tws_2025_113712 crossref_primary_10_1109_TMLCN_2025_3595125 crossref_primary_10_1016_j_cpb_2024_100432 crossref_primary_10_1007_s10018_024_00420_5 crossref_primary_10_1016_j_inffus_2024_102645 crossref_primary_10_1016_j_ins_2024_120663 crossref_primary_10_1016_j_inffus_2024_102889 crossref_primary_10_1016_j_tifs_2024_104396 crossref_primary_10_3390_rs17142526 crossref_primary_10_2478_amns_2025_0056 crossref_primary_10_3390_polym17111522 crossref_primary_10_1007_s10878_024_01243_6 crossref_primary_10_1080_10548408_2025_2502420 crossref_primary_10_1016_j_procs_2025_03_094 crossref_primary_10_1016_j_cstp_2025_101559 crossref_primary_10_1109_ACCESS_2024_3461798 crossref_primary_10_1007_s10462_025_11211_z crossref_primary_10_1038_s41598_025_01064_5 crossref_primary_10_1088_1361_6501_ad14e2 crossref_primary_10_1186_s40001_025_02660_x crossref_primary_10_1016_j_cherd_2025_03_018 crossref_primary_10_1088_1361_6501_add310 crossref_primary_10_3390_rs17050853 crossref_primary_10_3390_electronics12204218 crossref_primary_10_3390_app14209162 crossref_primary_10_1007_s44211_023_00403_8 crossref_primary_10_1177_14727978251337928
Cites_doi	10.1007/s13042-018-0836-3 10.1109/92.748202 10.1016/j.spasta.2016.07.003 10.1016/S0306-4379(00)00022-3 10.1016/B978-0-12-057650-0.50012-0 10.1016/j.spasta.2020.100407 10.1093/comjnl/9.4.373 10.1109/TKDE.2019.2903410 10.1007/BF02948829 10.1016/j.knosys.2020.106220 10.1007/s10618-005-0361-3 10.1016/j.patcog.2013.04.013 10.1109/TNNLS.2018.2853407 10.1109/TPAMI.2019.2924953 10.1007/s00357-005-0012-9 10.1007/s11222-007-9033-z 10.1016/j.asoc.2022.108584 10.1016/j.patcog.2012.11.017 10.1093/bioinformatics/btg288 10.1109/34.709614 10.1002/widm.1219 10.1109/TKDE.2019.2962412 10.1007/s00521-018-3641-8 10.1016/j.knosys.2014.04.008 10.1093/nar/gkr349 10.1109/TPAMI.2016.2615921 10.1093/bioinformatics/14.9.783 10.1016/j.neunet.2012.06.007 10.1007/3-540-28349-8_2 10.1093/comjnl/26.4.354 10.1109/TNSE.2018.2830822 10.1186/s12859-020-3453-6 10.1109/34.765656 10.1016/j.datak.2007.05.005 10.1002/j.1538-7305.1970.tb01770.x 10.1109/TPAMI.2006.227 10.1007/s00357-014-9161-z 10.1007/s10288-013-0228-1 10.1155/2018/2032461 10.1109/TPAMI.2014.2346173 10.1002/widm.53 10.1016/j.cageo.2018.11.003 10.1016/j.is.2021.101871 10.1109/TC.2018.2879332 10.1109/34.824819 10.1109/2.781637 10.3390/ijgi6010030 10.1007/s12652-021-03673-0 10.1023/A:1012801612483 10.1109/T-C.1971.223083 10.1109/TCYB.2014.2358564 10.1109/TCYB.2018.2794998 10.1007/BF00114265 10.1109/TPDS.2014.2355205 10.1109/TPAMI.2010.88 10.1007/978-3-642-56927-2 10.1016/j.neucom.2015.01.090 10.1016/j.procs.2020.04.004 10.1016/j.knosys.2014.03.013 10.1109/TNN.2005.845141 10.1016/j.spl.2020.108781 10.1002/9780470316801 10.1007/BF00058654 10.4018/IJSI.2020040101 10.1007/s00357-018-9259-9 10.1145/3299876 10.9781/ijimai.2020.03.001 10.1007/s10618-011-0221-2 10.1007/978-3-642-37456-2_14 10.1287/mnsc.31.6.647 10.1145/1102351.1102389 10.1007/978-3-030-44584-3_21 10.1109/CVPR42600.2020.01367 10.1007/3-540-36175-8_8 10.1609/aaai.v33i01.33018738 10.1109/NGCT.2015.7375113 10.1109/IMCEC46724.2019.8983946 10.1109/FUZZY.2004.1375399 10.1109/AIKE.2019.00041 10.1609/aaai.v35i10.17051 10.1109/SmartWorld.2018.00199 10.1109/ISIE.2019.8781307 10.1504/IJRAPIDM.2009.029382 10.1109/ICDM.2001.989504 10.1145/1183614.1183667 10.1007/978-3-642-33718-5_31 10.1109/CCOMS.2018.8463288 10.1145/3292500.3330929 10.1109/CSII.2018.00025 10.1145/3493700.3493727 10.1109/ISTEL.2010.5734151 10.1145/3447548.3467404 10.1145/584792.584877 10.1145/361219.361220 10.1007/s40745-015-0040-1 10.1007/BF02291173 10.1086/408956 10.1007/978-3-030-60796-8_37 10.3233/IDA-2007-11602 10.1109/COMPSAC.2018.00127 10.1109/CVPR.2005.89 10.1109/ICDE48307.2020.00184 10.1145/233269.233324 10.1007/BF01908075 10.1109/DEXA.2010.25 10.1109/CVPR.2005.50 10.1016/j.omega.2020.102370 10.1109/ICCV.2009.5459322 10.1109/LA-CCI47412.2019.9036754 10.1016/j.eswa.2019.03.031 10.1371/journal.pone.0141756 10.1109/ICMLC.2007.4370836 10.1109/FSKD.2009.205 10.1145/276304.276312 10.1007/BF02289588 10.1109/IJCNN48605.2020.9206722 10.1109/GrC.2012.6468689 10.1109/UPCON.2018.8596795 10.1073/pnas.122653799 10.1109/ICIP.2014.7025983 10.1109/RAICS.2011.6069433 10.1109/ICDM.2008.115 10.1137/1026034 10.1063/1.4908014 10.1007/BF01890115 10.1145/3534678.3539323 10.7551/mitpress/7503.003.0205 10.1109/IC4ME2.2018.8465616 10.1023/A:1009740529316 10.1038/2021034a0 10.1145/3195106.3195118 10.1109/ICDMW.2016.0123 10.1109/CSBW.2005.10 10.2307/2528688 10.1109/NoF50125.2020.9249194 10.1109/ICDM.2015.90 10.1109/GrC.2007.34 10.1016/j.eswa.2014.09.054 10.1109/WI-IAT.2012.9 10.1109/TASSP.1980.1163491 10.1109/CIBCB.2018.8404978 10.1016/0377-2217(86)90044-5 10.1109/CcS49175.2020.9231474 10.1016/j.epsr.2008.01.010 10.1109/WKDD.2010.123 10.1145/3097983.3098079 10.1007/978-3-319-63315-2_28
ContentType	Journal Article
Copyright	The Author(s), under exclusive licence to Springer Nature B.V. 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. COPYRIGHT 2023 Springer Copyright Springer Nature B.V. Aug 2023
Copyright_xml	– notice: The Author(s), under exclusive licence to Springer Nature B.V. 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. – notice: COPYRIGHT 2023 Springer – notice: Copyright Springer Nature B.V. Aug 2023
DBID	AAYXX CITATION 3V. 7SC 7WY 7WZ 7XB 87Z 8AL 8AO 8FD 8FE 8FG 8FK 8FL ABUWG AFKRA ALSLI ARAPS AZQEC BENPR BEZIV BGLVJ CCPQU CNYFK DWQXO E3H F2A FRNLG F~G GNUQQ HCIFZ JQ2 K60 K6~ K7- L.- L7M L~C L~D M0C M0N M1O P5Z P62 PHGZM PHGZT PKEHL PQBIZ PQBZA PQEST PQGLB PQQKQ PQUKI PRINS PRQQA PSYQQ Q9U
DOI	10.1007/s10462-022-10366-3
DatabaseName	CrossRef ProQuest Central (Corporate) Computer and Information Systems Abstracts ABI/INFORM Collection ABI/INFORM Global (PDF only) ProQuest Central (purchase pre-March 2016) ABI/INFORM Collection Computing Database (Alumni Edition) ProQuest Pharma Collection Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Central (Alumni) (purchase pre-March 2016) ABI/INFORM Collection (Alumni) ProQuest Central (Alumni) ProQuest Central UK/Ireland Social Science Premium Collection Advanced Technologies & Computer Science Collection ProQuest Central Essentials ProQuest Central Business Premium Collection Technology Collection ProQuest One Community College Library & Information Science Collection ProQuest Central Library & Information Sciences Abstracts (LISA) Library & Information Science Abstracts (LISA) Business Premium Collection (Alumni) ABI/INFORM Global (Corporate) ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection ProQuest Business Collection (Alumni Edition) ProQuest Business Collection Computer Science Database ABI/INFORM Professional Advanced Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional ABI/INFORM Global Computing Database Library Science Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Premium ProQuest One Academic ProQuest One Academic Middle East (New) ProQuest One Business ProQuest One Business (Alumni) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China ProQuest One Social Sciences ProQuest One Psychology ProQuest Central Basic
DatabaseTitle	CrossRef ProQuest Business Collection (Alumni Edition) ProQuest One Psychology Computer Science Database ProQuest Central Student Library and Information Science Abstracts (LISA) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection Computer and Information Systems Abstracts SciTech Premium Collection ProQuest Central China ABI/INFORM Complete ProQuest One Applied & Life Sciences Library & Information Science Collection ProQuest Central (New) Advanced Technologies & Aerospace Collection Business Premium Collection Social Science Premium Collection ABI/INFORM Global ProQuest One Academic Eastern Edition ProQuest Technology Collection ProQuest Business Collection ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ABI/INFORM Global (Corporate) ProQuest One Business Technology Collection Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest One Academic Middle East (New) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest Pharma Collection ProQuest Central ABI/INFORM Professional Advanced ProQuest Library Science ProQuest Central Korea Advanced Technologies Database with Aerospace ABI/INFORM Complete (Alumni Edition) ProQuest Computing ProQuest One Social Sciences ABI/INFORM Global (Alumni Edition) ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest SciTech Collection Computer and Information Systems Abstracts Professional Advanced Technologies & Aerospace Database ProQuest One Business (Alumni) ProQuest Central (Alumni) Business Premium Collection (Alumni)
DatabaseTitleList	ProQuest Business Collection (Alumni Edition)
Database_xml	– sequence: 1 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Computer Science
EISSN	1573-7462
EndPage	8264
ExternalDocumentID	A754967837 10_1007_s10462_022_10366_3
GrantInformation_xml	– fundername: Key Technologies Research and Development Program grantid: 2017YFE0111900; 2018YFB1003205 – fundername: Foundation for Innovation Groups of Basic Research in Gansu Province grantid: 20JR10RG304 funderid: http://dx.doi.org/10.13039/501100012555 – fundername: Gansu Education Department grantid: 2020B-214 funderid: http://dx.doi.org/10.13039/501100009590
GroupedDBID	-4Z -59 -5G -BR -EM -Y2 -~C .4S .86 .DC .VR 06D 0R~ 0VY 1N0 1SB 2.D 203 23N 28- 2J2 2JN 2JY 2KG 2LR 2P1 2VQ 2~H 30V 3V. 4.4 406 408 409 40D 40E 5GY 5QI 5VS 67Z 6J9 6NX 77K 7WY 8AO 8FE 8FG 8FL 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AAHNG AAIAL AAJKR AAJSJ AAKKN AANZL AAOBN AARHV AARTL AATVU AAUYE AAWCG AAYIU AAYQN AAYTO AAYZH ABAKF ABBBX ABBXA ABDZT ABECU ABEEZ ABFTD ABFTV ABHLI ABHQN ABIVO ABJNI ABJOX ABKCH ABKTR ABMNI ABMOR ABMQK ABNWP ABQBU ABQSL ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABUWG ABWNU ABXPI ACACY ACBXY ACGFS ACHSB ACHXU ACIHN ACKNC ACMDZ ACMLO ACOKC ACOMO ACREN ACSNA ACULB ACZOJ ADHHG ADHIR ADIMF ADINQ ADKNI ADKPE ADMLS ADRFC ADTPH ADURQ ADYFF ADYOE ADZKW AEAQA AEBTG AEFIE AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFEXP AFFNX AFGCZ AFGXO AFKRA AFLOW AFQWF AFWTZ AFYQB AFZKB AGAYW AGDGC AGGDS AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHSBF AHYZX AIAKS AIIXL AILAN AITGF AJBLW AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALSLI ALWAN AMKLP AMTXH AMXSW AMYLF AMYQR AOCGG ARAPS ARCSS ARMRJ ASPBG AVWKF AXYYD AYJHY AZFZN AZQEC B-. BA0 BBWZM BDATZ BENPR BEZIV BGLVJ BGNMA BPHCQ C24 C6C CAG CCPQU CNYFK COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP DWQXO EBLON EBS EDO EIOEI EJD ESBYG FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRNLG FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNUQQ GNWQR GQ6 GQ7 GQ8 GROUPED_ABI_INFORM_COMPLETE GXS H13 HCIFZ HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF HZ~ I-F I09 IAO IHE IJ- IKXTQ ITM IWAJR IXC IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ K60 K6V K6~ K7- KDC KOV KOW LAK LLZTM M0C M0N M1O M4Y MA- MK~ N2Q N9A NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM OVD P19 P62 P9O PF0 PQBIZ PQBZA PQQKQ PROAC PSYQQ PT5 Q2X QOK QOS R4E R89 R9I RHV RNI RNS ROL RPX RSV RZC RZE RZK S16 S1Z S26 S27 S28 S3B SAP SCJ SCLPG SCO SDH SDM SHX SISQX SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 T16 TEORI TSG TSK TSV TUC TUS U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WH7 WK8 YLTOR Z45 Z5O Z7R Z7X Z7Y Z7Z Z81 Z83 Z86 Z88 Z8M Z8N Z8R Z8S Z8T Z8U Z8W Z92 ZMTXR ~A9 ~EX 77I AAFWJ AASML AAYXX ABDBE ABFSG ACSTC ADHKG AEZWR AFFHD AFHIU AGQPQ AHPBZ AHWEU AIXLP AYFIA CITATION ICD PHGZM PHGZT PQGLB PRQQA 7SC 7XB 8AL 8FD 8FK E3H F2A JQ2 L.- L7M L~C L~D PKEHL PQEST PQUKI PRINS Q9U
ID	FETCH-LOGICAL-c358t-5fd1402dd90cd4a6c5a1652186f9f0ad5defe197e31e49653ba3d09bd23c63e03
IEDL.DBID	K7-
ISICitedReferencesCount	162
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000903993600003&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0269-2821
IngestDate	Sat Nov 15 15:52:05 EST 2025 Sat Nov 29 10:30:10 EST 2025 Tue Nov 18 22:24:16 EST 2025 Sat Nov 29 02:43:27 EST 2025 Fri Feb 21 02:43:10 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	8
Keywords	Divisive Agglomerative Similarity Hierarchical clustering Dissimilarity
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c358t-5fd1402dd90cd4a6c5a1652186f9f0ad5defe197e31e49653ba3d09bd23c63e03
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0003-4097-0709 0000-0001-8926-2039
PQID	2829976447
PQPubID	36790
PageCount	46
ParticipantIDs	proquest_journals_2829976447 gale_infotracacademiconefile_A754967837 crossref_primary_10_1007_s10462_022_10366_3 crossref_citationtrail_10_1007_s10462_022_10366_3 springer_journals_10_1007_s10462_022_10366_3
PublicationCentury	2000
PublicationDate	20230800 2023-08-00 20230801
PublicationDateYYYYMMDD	2023-08-01
PublicationDate_xml	– month: 8 year: 2023 text: 20230800
PublicationDecade	2020
PublicationPlace	Dordrecht
PublicationPlace_xml	– name: Dordrecht
PublicationSubtitle	An International Science and Engineering Journal
PublicationTitle	The Artificial intelligence review
PublicationTitleAbbrev	Artif Intell Rev
PublicationYear	2023
Publisher	Springer Netherlands Springer Springer Nature B.V
Publisher_xml	– name: Springer Netherlands – name: Springer – name: Springer Nature B.V
References	Li, Li, Qiu (CR92) 2017; 6 Zhou, Zhang, Feng (CR179) 2018 Yang, Grunsky, Cheng (CR164) 2019; 123 Bouguettaya, Yu, Liu (CR15) 2015; 42 Murtagh, Contreras (CR109) 2012; 2 Ros, Guillaume, Hajji (CR131) 2020; 204 Qin, Lewis, Noble (CR124) 2003; 19 Ishizaka, Lokman, Tasiou (CR68) 2020; 103 Zahn (CR167) 1971; 20 Johnson (CR75) 1967; 32 Lance, Williams (CR88) 1967; 9 CR163 CR39 Roux (CR132) 2018; 35 CR36 Narita, Hochin, Hayashi (CR114) 2020; 8 CR35 CR159 CR32 CR157 CR30 Li, Deng, Wang (CR91) 2014; 65 CR155 CR156 CR153 Brans, Vincke (CR16) 1985; 31 Lerato, Niesler (CR89) 2015; 10 Cai, Liu (CR19) 2020; 7 Kotsiantis, Pintelas (CR85) 2004; 1 Fisher (CR42) 1987; 2 Núñez-Valdéz, Solanki, Balakrishna (CR119) 2020; 6 Campello, Moulavi, Sander, Pei, Tseng, Cao (CR21) 2013 Abdi, Valentin (CR1) 2007; 2 CR173 CR174 Pang, Zhang, Zhang (CR121) 2019; 68 CR171 CR48 CR47 CR170 von Luxburg (CR99) 2007; 17 Forgy (CR43) 1965; 21 CR168 CR169 CR40 Halkidi, Batistakis, Vazirgiannis (CR58) 2001; 17 Sander, Qin, Lu, Whang, Jeon, Shim (CR137) 2003 CR165 Berkhin, Kogan, Nicholas, Teboulle (CR13) 2006 Alzate, Suykens (CR7) 2012; 35 Cheung, Zhang (CR31) 2019; 30 Jeon, Yoon (CR74) 2015; 26 Nikpour, Asadi (CR118) 2022; 13 Székely, Rizzo (CR145) 2005; 22 Jambu, Tan, Stern (CR72) 1989 Qin, Ma, Herawan (CR123) 2014; 67 Varshney, Muhuri, Lohani (CR154) 2022; 120 CR140 Yu, Hillebrand, Tewarie (CR166) 2015; 25 CR141 Redner, Walker (CR128) 1984; 26 Carpineto, Romano (CR23) 1996; 24 CR57 CR56 Parmar, Wu, Blackhurst (CR122) 2007; 63 CR54 CR138 CR135 Xiong, Wang, Mayers (CR160) 2012; 24 CR52 Lewis-Beck, Bryman, Liao (CR90) 2003 CR136 CR51 Frigui, Krishnapuram (CR46) 1999; 21 Tan, Steinbach, Karpatne (CR147) 2019 CR139 Wishart (CR158) 1969; 25 Chen, Song, Bai (CR26) 2011; 33 Lu, Wan (CR97) 2013; 46 Kaufman, Rousseeuw (CR80) 2009 Girvan, Newman (CR49) 2002; 99 He, Xu, Deng (CR62) 2002; 17 Kumar, Tripathy (CR86) 2009; 1 CR148 Murtagh, Contreras (CR110) 2017 Rocha, Dias (CR129) 2013; 11 CR149 Cheng, Zhu, Huang (CR28) 2019; 31 CR146 CR63 Sabarish, Karthi, Kumar (CR134) 2020; 171 CR144 CR60 CR143 Anderberg (CR8) 1973 Guha, Rastogi, Shim (CR55) 2000; 25 Everitt, Landau, Leese (CR41) 2001 Kaufman, Rousseeuw (CR79) 1990 Reddy, Vinzamuri, Aggarwal, Reddy (CR127) 2013 Hubert (CR65) 1973; 38 Neto, Sander, Campello (CR117) 2021; 33 Guan, Du (CR53) 1998; 14 Omran, Engelbrecht, Salman (CR120) 2007; 11 CR115 CR116 CR113 Karypis, Han, Kumar (CR78) 1999; 32 CR73 Cheng, Zhu, Huang (CR27) 2019; 10 CR71 Kohonen (CR84) 2001 CR2 Huang, Wang, Wu (CR64) 2020; 32 Tripathy, Ghosh (CR150) 2011; 2 Boley (CR14) 1998; 2 CR3 CR6 CR5 Zhu, Ting, Jin (CR180) 2022; 103 Myers, Rabiner, Rosenberg (CR112) 1980; 28 Chen, Cui, Wang (CR25) 2006; 12 CR126 CR87 CR125 Tripathy, Goyal, Chowdhury (CR151) 2017; 9 Barton, Bruna, Kordík (CR11) 2019; 13 CR83 CR81 Xu, Tian (CR161) 2015; 2 Hulot, Chiquet, Jaffrézic (CR67) 2020; 21 Agha (CR4) 1990 Brans, Vincke, Mareschal (CR17) 1986; 24 Ros, Guillaume (CR130) 2019; 128 He, Ray, Guan (CR61) 2019; 49 Zhao, Karypis, Fayyad (CR177) 2005; 10 Macnaughton-Smith, Williams, Dale (CR101) 1964; 202 Duran, Odell (CR37) 2013 Judd, McKinley, Jain (CR76) 1998; 20 CR12 Jain, Duin, Mao (CR70) 2000; 22 Zhang, Zhao, Wang (CR172) 2013; 46 Kernighan, Lin (CR82) 1970; 49 CR10 Jain, Dubes (CR69) 1988 CR96 CR94 CR178 CR93 CR175 Fränti, Virmajoki, Hautamäki (CR45) 2006; 28 CR176 Xu, Wunsch (CR162) 2005; 16 Golub, Loan (CR50) 1996 Day, Edelsbrunner (CR34) 1984; 1 Cai, Chen (CR18) 2015; 45 Lu, Hou, Chen (CR98) 2016; 173 Murtagh (CR108) 1983; 26 Averbuch-Elor, Bar, Cohen-Or (CR9) 2020; 42 Sisodia, Singh, Sisodia (CR142) 2012; 1 Hubert, Arabie (CR66) 1985; 2 Fouedjio (CR44) 2016; 18 Chakraborty, Paul, Das (CR24) 2020; 163 Karypis, Aggarwal, Kumar (CR77) 1999; 7 CR29 Murtagh, Legendre (CR111) 2014; 31 D’Urso, Vitale (CR38) 2020; 35 Tsekouras, Kotoulas, Tsirekis (CR152) 2008; 78 CR22 CR104 CR105 Han, Kamber, Pei (CR59) 2011; 5 CR102 CR103 CR100 Cai, Sun (CR20) 2011; 39 Liu, Latecki, Yan (CR95) 2015; 37 Courty, Flamary, Tuia (CR33) 2017; 39 CR106 CR107 D Sisodia (10366_CR142) 2012; 1 10366_CR40 D Chen (10366_CR25) 2006; 12 D Huang (10366_CR64) 2020; 32 M Jambu (10366_CR72) 1989 Y Lu (10366_CR98) 2016; 173 10366_CR135 10366_CR136 S Chakraborty (10366_CR24) 2020; 163 H Abdi (10366_CR1) 2007; 2 10366_CR138 10366_CR47 M Lewis-Beck (10366_CR90) 2003 10366_CR139 10366_CR48 G Karypis (10366_CR78) 1999; 32 10366_CR39 W Zhang (10366_CR172) 2013; 46 X Guan (10366_CR53) 1998; 14 M Roux (10366_CR132) 2018; 35 N Courty (10366_CR33) 2017; 39 JP Brans (10366_CR16) 1985; 31 F Murtagh (10366_CR108) 1983; 26 CT Zahn (10366_CR167) 1971; 20 JP Brans (10366_CR17) 1986; 24 K Narita (10366_CR114) 2020; 8 F Murtagh (10366_CR110) 2017 BS Duran (10366_CR37) 2013 10366_CR51 10366_CR52 10366_CR54 10366_CR125 10366_CR56 10366_CR126 10366_CR57 T Xiong (10366_CR160) 2012; 24 P Berkhin (10366_CR13) 2006 GA Agha (10366_CR4) 1990 C Carpineto (10366_CR23) 1996; 24 M Halkidi (10366_CR58) 2001; 17 B Tripathy (10366_CR150) 2011; 2 C Myers (10366_CR112) 1980; 28 J Yang (10366_CR164) 2019; 123 AK Jain (10366_CR69) 1988 H Liu (10366_CR95) 2015; 37 S Guha (10366_CR55) 2000; 25 S Nikpour (10366_CR118) 2022; 13 10366_CR153 10366_CR155 10366_CR156 B Tripathy (10366_CR151) 2017; 9 10366_CR157 10366_CR22 10366_CR159 Y Zhu (10366_CR180) 2022; 103 D Xu (10366_CR161) 2015; 2 Y Cheung (10366_CR31) 2019; 30 F Fouedjio (10366_CR44) 2016; 18 T Barton (10366_CR11) 2019; 13 W Chen (10366_CR26) 2011; 33 H Qin (10366_CR123) 2014; 67 D Cai (10366_CR18) 2015; 45 Y Cai (10366_CR20) 2011; 39 10366_CR140 10366_CR141 SC Johnson (10366_CR75) 1967; 32 C Rocha (10366_CR129) 2013; 11 10366_CR143 10366_CR30 10366_CR144 Q Cai (10366_CR19) 2020; 7 10366_CR32 10366_CR146 H Frigui (10366_CR46) 1999; 21 10366_CR148 10366_CR35 P Tan (10366_CR147) 2019 10366_CR149 10366_CR36 10366_CR29 J Sander (10366_CR137) 2003 Z He (10366_CR62) 2002; 17 B Everitt (10366_CR41) 2001 10366_CR170 D Boley (10366_CR14) 1998; 2 RA Redner (10366_CR128) 1984; 26 10366_CR171 10366_CR81 10366_CR173 10366_CR174 10366_CR83 CK Reddy (10366_CR127) 2013 10366_CR175 F Ros (10366_CR131) 2020; 204 10366_CR176 A Hulot (10366_CR67) 2020; 21 G Karypis (10366_CR77) 1999; 7 10366_CR178 S Kotsiantis (10366_CR85) 2004; 1 10366_CR87 P D’Urso (10366_CR38) 2020; 35 AK Jain (10366_CR70) 2000; 22 M Yu (10366_CR166) 2015; 25 MR Anderberg (10366_CR8) 1973 D Cheng (10366_CR28) 2019; 31 10366_CR93 10366_CR163 10366_CR94 10366_CR165 10366_CR96 R Xu (10366_CR162) 2005; 16 10366_CR10 10366_CR168 10366_CR169 10366_CR12 D Parmar (10366_CR122) 2007; 63 GJ Székely (10366_CR145) 2005; 22 G Tsekouras (10366_CR152) 2008; 78 L Hubert (10366_CR66) 1985; 2 M Li (10366_CR91) 2014; 65 M Girvan (10366_CR49) 2002; 99 J Han (10366_CR59) 2011; 5 P Macnaughton-Smith (10366_CR101) 1964; 202 R Zhou (10366_CR179) 2018 10366_CR60 F Murtagh (10366_CR109) 2012; 2 L Hubert (10366_CR65) 1973; 38 Y Lu (10366_CR97) 2013; 46 10366_CR63 AK Varshney (10366_CR154) 2022; 120 10366_CR113 GH Golub (10366_CR50) 1996 F Ros (10366_CR130) 2019; 128 10366_CR115 10366_CR116 L Lerato (10366_CR89) 2015; 10 B Sabarish (10366_CR134) 2020; 171 D Wishart (10366_CR158) 1969; 25 L He (10366_CR61) 2019; 49 P Fränti (10366_CR45) 2006; 28 H Averbuch-Elor (10366_CR9) 2020; 42 MGH Omran (10366_CR120) 2007; 11 L Kaufman (10366_CR79) 1990 GN Lance (10366_CR88) 1967; 9 F Murtagh (10366_CR111) 2014; 31 A Bouguettaya (10366_CR15) 2015; 42 U von Luxburg (10366_CR99) 2007; 17 J Qin (10366_CR124) 2003; 19 D Judd (10366_CR76) 1998; 20 BW Kernighan (10366_CR82) 1970; 49 L Kaufman (10366_CR80) 2009 10366_CR5 10366_CR2 10366_CR3 10366_CR71 Y Zhao (10366_CR177) 2005; 10 10366_CR6 10366_CR73 10366_CR100 C Alzate (10366_CR7) 2012; 35 DH Fisher (10366_CR42) 1987; 2 T Kohonen (10366_CR84) 2001 10366_CR102 Y Jeon (10366_CR74) 2015; 26 10366_CR103 10366_CR104 ER Núñez-Valdéz (10366_CR119) 2020; 6 10366_CR105 S Li (10366_CR92) 2017; 6 10366_CR106 10366_CR107 D Cheng (10366_CR27) 2019; 10 A Ishizaka (10366_CR68) 2020; 103 RJGB Campello (10366_CR21) 2013 N Pang (10366_CR121) 2019; 68 ACA Neto (10366_CR117) 2021; 33 WH Day (10366_CR34) 1984; 1 P Kumar (10366_CR86) 2009; 1 EW Forgy (10366_CR43) 1965; 21
References_xml	– ident: CR22 – volume: 10 start-page: 1591 issue: 7 year: 2019 end-page: 1602 ident: CR27 article-title: A hierarchical clustering algorithm based on noise removal publication-title: Int J Mach Learn Cybern doi: 10.1007/s13042-018-0836-3 – ident: CR173 – volume: 2 start-page: 193 issue: 1 year: 1985 end-page: 218 ident: CR66 article-title: Comparing partitions publication-title: J Classif – volume: 7 start-page: 69 issue: 1 year: 1999 end-page: 79 ident: CR77 article-title: Multilevel hypergraph partitioning: applications in VLSI domain publication-title: IEEE Trans Very Large Scale Integr Syst doi: 10.1109/92.748202 – ident: CR39 – volume: 1 start-page: 73 issue: 1 year: 2004 end-page: 81 ident: CR85 article-title: Recent advances in clustering: a brief survey publication-title: WSEAS Trans Inf Sci Appl – volume: 26 start-page: 195 issue: 2 year: 1984 end-page: 239 ident: CR128 article-title: Mixture densities, maximum likelihood and the EM algorithm publication-title: SIAM Rev – volume: 78 start-page: 1494 issue: 9 year: 2008 end-page: 1510 ident: CR152 article-title: A pattern recognition methodology for evaluation of load profiles and typical days of large electricity customers publication-title: Electr Power Syst Res – ident: CR51 – volume: 18 start-page: 333 year: 2016 end-page: 351 ident: CR44 article-title: A hierarchical clustering method for multivariate geostatistical data publication-title: Spat Stat doi: 10.1016/j.spasta.2016.07.003 – ident: CR115 – ident: CR138 – ident: CR135 – volume: 25 start-page: 345 issue: 5 year: 2000 end-page: 366 ident: CR55 article-title: ROCK: a robust clustering algorithm for categorical attributes publication-title: Inf Syst doi: 10.1016/S0306-4379(00)00022-3 – ident: CR54 – ident: CR106 – year: 1973 ident: CR8 publication-title: Chapter 6–hierarchical clustering methods, probability and mathematical statistics: a series of monographs and textbooks doi: 10.1016/B978-0-12-057650-0.50012-0 – ident: CR144 – volume: 35 start-page: 407 issue: 100 year: 2020 ident: CR38 article-title: A robust hierarchical clustering for georeferenced data publication-title: Spat Stat doi: 10.1016/j.spasta.2020.100407 – ident: CR71 – volume: 9 start-page: 373 issue: 4 year: 1967 end-page: 380 ident: CR88 article-title: A general theory of classificatory sorting strategies: 1. Hierarchical systems publication-title: Comput J doi: 10.1093/comjnl/9.4.373 – year: 1996 ident: CR50 publication-title: Matrix computations – volume: 32 start-page: 1212 issue: 6 year: 2020 end-page: 1226 ident: CR64 article-title: Ultra-scalable spectral clustering and ensemble clustering publication-title: IEEE Trans Knowl Data Eng doi: 10.1109/TKDE.2019.2903410 – volume: 17 start-page: 611 issue: 5 year: 2002 end-page: 624 ident: CR62 article-title: Squeezer: an efficient algorithm for clustering categorical data publication-title: J Comput Sci Technol doi: 10.1007/BF02948829 – volume: 1 start-page: 189 issue: 2 year: 2009 end-page: 207 ident: CR86 article-title: MMeR: an algorithm for clustering heterogeneous data using rough set theory publication-title: Int J Rapid Manuf – volume: 204 start-page: 220 issue: 106 year: 2020 ident: CR131 article-title: KdMutual: a novel clustering algorithm combining mutual neighboring and hierarchical approaches using a new selection criterion publication-title: Knowl Based Syst doi: 10.1016/j.knosys.2020.106220 – volume: 10 start-page: 141 issue: 2 year: 2005 end-page: 168 ident: CR177 article-title: Hierarchical clustering algorithms for document datasets publication-title: Data Min Knowl Discov doi: 10.1007/s10618-005-0361-3 – volume: 11 start-page: 583 issue: 6 year: 2007 end-page: 605 ident: CR120 article-title: An overview of clustering methods publication-title: Intell Data Anal – volume: 46 start-page: 3056 issue: 11 year: 2013 end-page: 3065 ident: CR172 article-title: Agglomerative clustering via maximum incremental path integral publication-title: Pattern Recogn doi: 10.1016/j.patcog.2013.04.013 – ident: CR178 – volume: 30 start-page: 876 issue: 3 year: 2019 end-page: 890 ident: CR31 article-title: Fast and accurate hierarchical clustering based on growing multilayer topology training publication-title: IEEE Trans Neural Netw Learn Syst doi: 10.1109/TNNLS.2018.2853407 – ident: CR153 – volume: 42 start-page: 1791 issue: 7 year: 2020 end-page: 1797 ident: CR9 article-title: Border-peeling clustering publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2019.2924953 – ident: CR170 – ident: CR57 – ident: CR60 – start-page: 75 year: 2003 end-page: 87 ident: CR137 article-title: Automatic extraction of clusters from hierarchical clustering representations publication-title: Advances in knowledge discovery and data mining – ident: CR36 – volume: 202 start-page: 1034 issue: 4936 year: 1964 end-page: 1035 ident: CR101 article-title: Dissimilarity analysis: a new technique of hierarchical sub-division publication-title: Nature – ident: CR5 – volume: 22 start-page: 151 issue: 2 year: 2005 end-page: 183 ident: CR145 article-title: Hierarchical clustering via joint between-within distances: extending Ward’s minimum variance method publication-title: J Classif doi: 10.1007/s00357-005-0012-9 – volume: 17 start-page: 395 issue: 4 year: 2007 end-page: 416 ident: CR99 article-title: A tutorial on spectral clustering publication-title: Stat Comput doi: 10.1007/s11222-007-9033-z – volume: 25 start-page: 023107 issue: 2 year: 2015 ident: CR166 article-title: Hierarchical clustering in minimum spanning trees publication-title: Chaos – year: 2013 ident: CR37 publication-title: Cluster analysis: a survey – volume: 120 start-page: 584 issue: 108 year: 2022 ident: CR154 article-title: PIFHC: the probabilistic intuitionistic fuzzy hierarchical clustering algorithm publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2022.108584 – ident: CR126 – volume: 2 start-page: 165 issue: 2 year: 2015 end-page: 193 ident: CR161 article-title: A comprehensive survey of clustering algorithms publication-title: Ann Data Sci – ident: CR100 – volume: 46 start-page: 1227 issue: 5 year: 2013 end-page: 1239 ident: CR97 article-title: PHA: a fast potential-based hierarchical agglomerative clustering method publication-title: Pattern Recognit doi: 10.1016/j.patcog.2012.11.017 – ident: CR47 – volume: 19 start-page: 2097 issue: 16 year: 2003 end-page: 2104 ident: CR124 article-title: Kernel hierarchical gene clustering from microarray expression data publication-title: Bioinformatics doi: 10.1093/bioinformatics/btg288 – volume: 20 start-page: 871 issue: 8 year: 1998 end-page: 876 ident: CR76 article-title: Large-scale parallel data clustering publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/34.709614 – year: 2017 ident: CR110 article-title: Algorithms for hierarchical clustering: an overview, II publication-title: Wiley Interdiscip Rev Data Min Knowl Discov doi: 10.1002/widm.1219 – ident: CR156 – ident: CR30 – ident: CR171 – ident: CR10 – volume: 33 start-page: 3075 issue: 8 year: 2021 end-page: 3089 ident: CR117 article-title: Efficient computation and visualization of multiple density-based clustering hierarchies publication-title: IEEE Trans Knowl Data Eng doi: 10.1109/TKDE.2019.2962412 – volume: 31 start-page: 8051 issue: 11 year: 2019 end-page: 8068 ident: CR28 article-title: A local cores-based hierarchical clustering algorithm for data sets with complex structures publication-title: Neural Comput Appl doi: 10.1007/s00521-018-3641-8 – volume: 65 start-page: 60 year: 2014 end-page: 71 ident: CR91 article-title: Hierarchical clustering algorithm for categorical data using a probabilistic rough set model publication-title: Knowl Based Syst doi: 10.1016/j.knosys.2014.04.008 – year: 2019 ident: CR147 publication-title: Introduction to data mining – ident: CR6 – volume: 39 start-page: e95 issue: 14 year: 2011 end-page: e95 ident: CR20 article-title: ESPRIT-tree: hierarchical clustering analysis of millions of 16s rRNA pyrosequences in quasilinear computational time publication-title: Nucleic Acids Res doi: 10.1093/nar/gkr349 – volume: 39 start-page: 1853 issue: 9 year: 2017 end-page: 1865 ident: CR33 article-title: Optimal transport for domain adaptation publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2016.2615921 – volume: 14 start-page: 783 issue: 9 year: 1998 end-page: 788 ident: CR53 article-title: Domain identification by clustering sequence alignments publication-title: Bioinformatics doi: 10.1093/bioinformatics/14.9.783 – ident: CR63 – volume: 35 start-page: 21 issue: C year: 2012 end-page: 30 ident: CR7 article-title: Hierarchical kernel spectral clustering publication-title: Neural Netw doi: 10.1016/j.neunet.2012.06.007 – start-page: 25 year: 2006 end-page: 71 ident: CR13 article-title: A survey of clustering data mining techniques publication-title: Grouping multidimensional data–recent advances in clustering doi: 10.1007/3-540-28349-8_2 – year: 1988 ident: CR69 publication-title: Algorithms for clustering data – ident: CR165 – ident: CR94 – volume: 26 start-page: 354 issue: 4 year: 1983 end-page: 359 ident: CR108 article-title: A survey of recent advances in hierarchical clustering algorithms publication-title: Comput J doi: 10.1093/comjnl/26.4.354 – volume: 7 start-page: 421 issue: 1 year: 2020 end-page: 434 ident: CR19 article-title: Hierarchical clustering of bipartite networks based on multiobjective optimization publication-title: IEEE Trans Netw Sci Eng doi: 10.1109/TNSE.2018.2830822 – volume: 1 start-page: 7 issue: 1 year: 1984 end-page: 24 ident: CR34 article-title: Efficient algorithms for agglomerative hierarchical clustering methods publication-title: J Classif – volume: 21 start-page: 120 issue: 1 year: 2020 ident: CR67 article-title: Fast tree aggregation for consensus hierarchical clustering publication-title: BMC Bioinform doi: 10.1186/s12859-020-3453-6 – ident: CR103 – ident: CR176 – volume: 21 start-page: 450 issue: 5 year: 1999 end-page: 465 ident: CR46 article-title: A robust competitive clustering algorithm with applications in computer vision publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/34.765656 – ident: CR3 – start-page: 87 year: 2013 end-page: 110 ident: CR127 article-title: A survey of partitional and hierarchical clustering algorithms publication-title: Data clustering: algorithms and applications – volume: 12 start-page: 149 issue: 3 year: 2006 end-page: 159 ident: CR25 article-title: A rough set-based hierarchical clustering algorithm for categorical data publication-title: Int J Inf Technol – ident: CR52 – ident: CR139 – volume: 2 start-page: 325 issue: 4 year: 1998 end-page: 344 ident: CR14 article-title: Principal direction divisive partitioning publication-title: Data Min Knowl Disc – volume: 63 start-page: 879 issue: 3 year: 2007 end-page: 893 ident: CR122 article-title: MMR: an algorithm for clustering categorical data using rough set theory publication-title: Data Knowl Eng doi: 10.1016/j.datak.2007.05.005 – volume: 5 start-page: 83 issue: 4 year: 2011 end-page: 124 ident: CR59 article-title: Data mining concepts and techniques: third edition publication-title: Morgan Kaufmann Ser Data Manag Syst – year: 2009 ident: CR80 publication-title: Finding groups in data: an introduction to cluster analysis – ident: CR159 – ident: CR83 – volume: 49 start-page: 291 issue: 2 year: 1970 end-page: 307 ident: CR82 article-title: An efficient heuristic procedure for partitioning graphs publication-title: Bell Syst Tech J doi: 10.1002/j.1538-7305.1970.tb01770.x – volume: 28 start-page: 1875 issue: 11 year: 2006 end-page: 1881 ident: CR45 article-title: Fast agglomerative clustering using a k-nearest neighbor graph publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2006.227 – ident: CR125 – ident: CR148 – ident: CR102 – volume: 9 start-page: 25 issue: 8 year: 2017 ident: CR151 article-title: MMeMeR: an algorithm for clustering heterogeneous data using rough set theory publication-title: Int J Intell Syst Appl – year: 2001 ident: CR41 publication-title: Cluster analysis – ident: CR93 – volume: 31 start-page: 274 issue: 3 year: 2014 end-page: 295 ident: CR111 article-title: Ward’s hierarchical agglomerative clustering method: which algorithms implement Ward’s criterion? publication-title: J Classif doi: 10.1007/s00357-014-9161-z – volume: 11 start-page: 253 issue: 3 year: 2013 end-page: 273 ident: CR129 article-title: MPOC: an agglomerative algorithm for multicriteria partially ordered clustering publication-title: 4OR doi: 10.1007/s10288-013-0228-1 – ident: CR87 – year: 2003 ident: CR90 publication-title: The Sage encyclopedia of social science research methods – ident: CR12 – volume: 25 start-page: 165 year: 1969 end-page: 170 ident: CR158 article-title: An algorithm for hierarchical classifications publication-title: Biometrics – volume: 32 start-page: 241 issue: 3 year: 1967 end-page: 254 ident: CR75 article-title: Hierarchical clustering schemes publication-title: Psychometrika – ident: CR35 – ident: CR29 – volume: 21 start-page: 768 year: 1965 end-page: 769 ident: CR43 article-title: Cluster analysis of multivariate data: efficiency versus interpretability of classifications publication-title: Biometrics – volume: 2 start-page: 651 issue: 4 year: 2007 end-page: 657 ident: CR1 article-title: Multiple correspondence analysis publication-title: Encycl Meas Stat – year: 2018 ident: CR179 article-title: A novel hierarchical clustering algorithm based on density peaks for complex datasets publication-title: Complex doi: 10.1155/2018/2032461 – volume: 37 start-page: 541 issue: 3 year: 2015 end-page: 554 ident: CR95 article-title: Dense subgraph partition of positive hypergraphs publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2014.2346173 – volume: 2 start-page: 86 issue: 1 year: 2012 end-page: 97 ident: CR109 article-title: Algorithms for hierarchical clustering: an overview publication-title: Wiley Interdiscip Rev Data Min Knowl Discov doi: 10.1002/widm.53 – volume: 42 start-page: 2785 issue: 5 year: 2015 end-page: 2797 ident: CR15 article-title: Efficient agglomerative hierarchical clustering publication-title: Expert Syst Appl – ident: CR140 – ident: CR163 – volume: 123 start-page: 10 year: 2019 end-page: 19 ident: CR164 article-title: A novel hierarchical clustering analysis method based on Kullback–Leibler divergence and application on dalaimiao geochemical exploration data publication-title: Comput Geosci doi: 10.1016/j.cageo.2018.11.003 – start-page: 160 year: 2013 end-page: 172 ident: CR21 article-title: Density-based clustering based on hierarchical density estimates publication-title: Advances in knowledge discovery and data mining – ident: CR174 – volume: 103 start-page: 102370 year: 2020 ident: CR68 article-title: A stochastic multi-criteria divisive hierarchical clustering algorithm publication-title: Omega – ident: CR96 – volume: 103 start-page: 101871 issue: C year: 2022 ident: CR180 article-title: Hierarchical clustering that takes advantage of both density-peak and density-connectivity publication-title: Inf Syst doi: 10.1016/j.is.2021.101871 – volume: 68 start-page: 542 issue: 4 year: 2019 end-page: 555 ident: CR121 article-title: Parallel hierarchical subspace clustering of categorical data publication-title: IEEE Trans Comput doi: 10.1109/TC.2018.2879332 – volume: 31 start-page: 647 issue: 6 year: 1985 end-page: 656 ident: CR16 article-title: Note—a preference ranking organisation method: (the PROMETHEE method for multiple criteria decision-making) publication-title: Manag Sci – volume: 99 start-page: 7821 issue: 12 year: 2002 end-page: 7826 ident: CR49 article-title: Community structure in social and biological networks publication-title: Proc Natl Acad Sci USA – volume: 22 start-page: 4 issue: 1 year: 2000 end-page: 37 ident: CR70 article-title: Statistical pattern recognition: a review publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/34.824819 – ident: CR157 – ident: CR116 – volume: 32 start-page: 68 issue: 8 year: 1999 end-page: 75 ident: CR78 article-title: Chameleon: hierarchical clustering using dynamic modeling publication-title: Computer doi: 10.1109/2.781637 – ident: CR136 – volume: 128 start-page: 96 year: 2019 end-page: 108 ident: CR130 article-title: A hierarchical clustering algorithm and an improvement of the single linkage criterion to deal with noise publication-title: Expert Syst Appl – ident: CR32 – volume: 6 start-page: 30 issue: 1 year: 2017 ident: CR92 article-title: A novel divisive hierarchical clustering algorithm for geospatial analysis publication-title: ISPRS Int J Geo-Inf doi: 10.3390/ijgi6010030 – volume: 13 start-page: 2983 issue: 6 year: 2022 end-page: 3003 ident: CR118 article-title: A dynamic hierarchical incremental learning-based supervised clustering for data stream with considering concept drift publication-title: J Ambient Intell Humaniz Comput doi: 10.1007/s12652-021-03673-0 – volume: 17 start-page: 107 issue: 2–3 year: 2001 end-page: 145 ident: CR58 article-title: On clustering validation techniques publication-title: J Intell Inf Syst doi: 10.1023/A:1012801612483 – ident: CR81 – volume: 38 start-page: 47 issue: 1 year: 1973 end-page: 62 ident: CR65 article-title: Monotone invariant clustering procedures publication-title: Psychometrika – ident: CR105 – volume: 20 start-page: 68 issue: 1 year: 1971 end-page: 86 ident: CR167 article-title: Graph-theoretical methods for detecting and describing gestalt clusters publication-title: IEEE Trans Comput doi: 10.1109/T-C.1971.223083 – ident: CR168 – volume: 45 start-page: 1669 issue: 8 year: 2015 end-page: 1680 ident: CR18 article-title: Large scale spectral clustering via landmark-based sparse representation publication-title: IEEE Trans Cybern doi: 10.1109/TCYB.2014.2358564 – ident: CR143 – year: 1990 ident: CR4 publication-title: ACTORS—a model of concurrent computation in distributed systems. MIT Press series in artificial intelligence – ident: CR175 – volume: 49 start-page: 1058 issue: 3 year: 2019 end-page: 1071 ident: CR61 article-title: Fast large-scale spectral clustering via explicit feature mapping publication-title: IEEE Trans Cybern doi: 10.1109/TCYB.2018.2794998 – year: 1989 ident: CR72 publication-title: Exploration informatique et statistique des données – volume: 2 start-page: 139 issue: 2 year: 1987 end-page: 172 ident: CR42 article-title: Knowledge acquisition via incremental conceptual clustering publication-title: Mach Learn doi: 10.1007/BF00114265 – volume: 26 start-page: 2534 issue: 9 year: 2015 end-page: 2548 ident: CR74 article-title: Multi-threaded hierarchical clustering by parallel nearest-neighbor chaining publication-title: IEEE Trans Parallel Distrib Syst doi: 10.1109/TPDS.2014.2355205 – volume: 10 start-page: e0141756 issue: 10 year: 2015 ident: CR89 article-title: Clustering acoustic segments using multi-stage agglomerative hierarchical clustering publication-title: PLoS ONE – volume: 33 start-page: 568 issue: 3 year: 2011 end-page: 586 ident: CR26 article-title: Parallel spectral clustering in distributed systems publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2010.88 – year: 2001 ident: CR84 publication-title: Self-organizing maps, third edition. Springer series in information sciences doi: 10.1007/978-3-642-56927-2 – volume: 173 start-page: 3 year: 2016 end-page: 8 ident: CR98 article-title: A novel travel-time based similarity measure for hierarchical clustering publication-title: Neurocomputing doi: 10.1016/j.neucom.2015.01.090 – ident: CR2 – volume: 171 start-page: 32 year: 2020 end-page: 41 ident: CR134 article-title: Graph similarity-based hierarchical clustering of trajectory data publication-title: Procedia Comput Sci doi: 10.1016/j.procs.2020.04.004 – ident: CR113 – volume: 1 start-page: 82 issue: 3 year: 2012 end-page: 87 ident: CR142 article-title: Clustering techniques: a brief survey of different clustering algorithms publication-title: Int J Latest Trends Eng Technol – volume: 67 start-page: 401 year: 2014 end-page: 411 ident: CR123 article-title: MGR: an information theory based hierarchical divisive clustering algorithm for categorical data publication-title: Knowl Based Syst doi: 10.1016/j.knosys.2014.03.013 – ident: CR56 – volume: 28 start-page: 623 issue: 6 year: 1980 end-page: 635 ident: CR112 article-title: Performance tradeoffs in dynamic time warping algorithms for isolated word recognition publication-title: IEEE Trans Acoust Speech Signal Process – volume: 24 start-page: 228 issue: 2 year: 1986 end-page: 238 ident: CR17 article-title: How to select and how to rank projects: the PROMETHEE method publication-title: Eur J Oper Res – ident: CR40 – volume: 16 start-page: 645 issue: 3 year: 2005 end-page: 678 ident: CR162 article-title: Survey of clustering algorithms publication-title: IEEE Trans Neural Netw doi: 10.1109/TNN.2005.845141 – ident: CR169 – volume: 163 start-page: 781 issue: 108 year: 2020 ident: CR24 article-title: Hierarchical clustering with optimal transport publication-title: Stat Probab Lett doi: 10.1016/j.spl.2020.108781 – ident: CR104 – ident: CR146 – ident: CR149 – year: 1990 ident: CR79 publication-title: Finding groups in data: an introduction to cluster analysis doi: 10.1002/9780470316801 – volume: 24 start-page: 95 issue: 2 year: 1996 end-page: 122 ident: CR23 article-title: A lattice conceptual clustering system and its application to browsing retrieval publication-title: Mach Learn doi: 10.1007/BF00058654 – ident: CR48 – ident: CR73 – ident: CR155 – volume: 8 start-page: 1 issue: 2 year: 2020 end-page: 22 ident: CR114 article-title: Incremental hierarchical clustering for data insertion and its evaluation publication-title: Int J Softw Innov doi: 10.4018/IJSI.2020040101 – volume: 35 start-page: 345 issue: 2 year: 2018 end-page: 366 ident: CR132 article-title: A comparative study of divisive and agglomerative hierarchical clustering algorithms publication-title: J Classif doi: 10.1007/s00357-018-9259-9 – volume: 13 start-page: 10 issue: 1 year: 2019 ident: CR11 article-title: Chameleon 2: an improved graph-based clustering algorithm publication-title: ACM Trans Knowl Discov Data doi: 10.1145/3299876 – volume: 6 start-page: 1 issue: 2 year: 2020 end-page: 15 ident: CR119 article-title: Incremental hierarchical clustering driven automatic annotations for unifying IoT streaming data publication-title: Int J Interact Multim Artif Intell doi: 10.9781/ijimai.2020.03.001 – volume: 24 start-page: 103 issue: 1 year: 2012 end-page: 135 ident: CR160 article-title: DHCC: divisive hierarchical clustering of categorical data publication-title: Data Min Knowl Discov doi: 10.1007/s10618-011-0221-2 – ident: CR107 – ident: CR141 – volume: 2 start-page: 314 issue: 3 year: 2011 end-page: 326 ident: CR150 article-title: SSDR: an algorithm for clustering categorical data using rough set theory publication-title: Adv Appl Sci Res – start-page: 160 volume-title: Advances in knowledge discovery and data mining year: 2013 ident: 10366_CR21 doi: 10.1007/978-3-642-37456-2_14 – volume: 31 start-page: 647 issue: 6 year: 1985 ident: 10366_CR16 publication-title: Manag Sci doi: 10.1287/mnsc.31.6.647 – volume-title: Exploration informatique et statistique des données year: 1989 ident: 10366_CR72 – volume: 2 start-page: 139 issue: 2 year: 1987 ident: 10366_CR42 publication-title: Mach Learn doi: 10.1007/BF00114265 – volume: 24 start-page: 103 issue: 1 year: 2012 ident: 10366_CR160 publication-title: Data Min Knowl Discov doi: 10.1007/s10618-011-0221-2 – ident: 10366_CR63 doi: 10.1145/1102351.1102389 – ident: 10366_CR73 doi: 10.1007/978-3-030-44584-3_21 – ident: 10366_CR169 doi: 10.1109/CVPR42600.2020.01367 – volume: 28 start-page: 1875 issue: 11 year: 2006 ident: 10366_CR45 publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2006.227 – ident: 10366_CR100 – start-page: 75 volume-title: Advances in knowledge discovery and data mining year: 2003 ident: 10366_CR137 doi: 10.1007/3-540-36175-8_8 – volume: 18 start-page: 333 year: 2016 ident: 10366_CR44 publication-title: Spat Stat doi: 10.1016/j.spasta.2016.07.003 – ident: 10366_CR94 doi: 10.1609/aaai.v33i01.33018738 – volume: 8 start-page: 1 issue: 2 year: 2020 ident: 10366_CR114 publication-title: Int J Softw Innov doi: 10.4018/IJSI.2020040101 – ident: 10366_CR81 doi: 10.1109/NGCT.2015.7375113 – ident: 10366_CR93 doi: 10.1109/IMCEC46724.2019.8983946 – ident: 10366_CR39 doi: 10.1109/FUZZY.2004.1375399 – ident: 10366_CR115 doi: 10.1109/AIKE.2019.00041 – ident: 10366_CR96 doi: 10.1609/aaai.v35i10.17051 – volume: 11 start-page: 253 issue: 3 year: 2013 ident: 10366_CR129 publication-title: 4OR doi: 10.1007/s10288-013-0228-1 – ident: 10366_CR148 doi: 10.1109/SmartWorld.2018.00199 – volume: 33 start-page: 568 issue: 3 year: 2011 ident: 10366_CR26 publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2010.88 – volume: 31 start-page: 274 issue: 3 year: 2014 ident: 10366_CR111 publication-title: J Classif doi: 10.1007/s00357-014-9161-z – ident: 10366_CR5 doi: 10.1109/ISIE.2019.8781307 – ident: 10366_CR140 – volume: 6 start-page: 30 issue: 1 year: 2017 ident: 10366_CR92 publication-title: ISPRS Int J Geo-Inf doi: 10.3390/ijgi6010030 – volume: 63 start-page: 879 issue: 3 year: 2007 ident: 10366_CR122 publication-title: Data Knowl Eng doi: 10.1016/j.datak.2007.05.005 – volume: 1 start-page: 189 issue: 2 year: 2009 ident: 10366_CR86 publication-title: Int J Rapid Manuf doi: 10.1504/IJRAPIDM.2009.029382 – ident: 10366_CR30 doi: 10.1109/ICDM.2001.989504 – ident: 10366_CR135 doi: 10.1145/1183614.1183667 – volume: 10 start-page: 141 issue: 2 year: 2005 ident: 10366_CR177 publication-title: Data Min Knowl Discov doi: 10.1007/s10618-005-0361-3 – volume: 9 start-page: 25 issue: 8 year: 2017 ident: 10366_CR151 publication-title: Int J Intell Syst Appl – ident: 10366_CR171 doi: 10.1007/978-3-642-33718-5_31 – ident: 10366_CR36 doi: 10.1109/CCOMS.2018.8463288 – ident: 10366_CR103 doi: 10.1145/3292500.3330929 – volume-title: Chapter 6–hierarchical clustering methods, probability and mathematical statistics: a series of monographs and textbooks year: 1973 ident: 10366_CR8 doi: 10.1016/B978-0-12-057650-0.50012-0 – volume: 31 start-page: 8051 issue: 11 year: 2019 ident: 10366_CR28 publication-title: Neural Comput Appl doi: 10.1007/s00521-018-3641-8 – ident: 10366_CR40 – ident: 10366_CR113 doi: 10.1109/CSII.2018.00025 – volume: 46 start-page: 3056 issue: 11 year: 2013 ident: 10366_CR172 publication-title: Pattern Recogn doi: 10.1016/j.patcog.2013.04.013 – volume: 32 start-page: 68 issue: 8 year: 1999 ident: 10366_CR78 publication-title: Computer doi: 10.1109/2.781637 – volume: 22 start-page: 4 issue: 1 year: 2000 ident: 10366_CR70 publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/34.824819 – volume: 65 start-page: 60 year: 2014 ident: 10366_CR91 publication-title: Knowl Based Syst doi: 10.1016/j.knosys.2014.04.008 – ident: 10366_CR139 – ident: 10366_CR35 doi: 10.1145/3493700.3493727 – ident: 10366_CR71 doi: 10.1109/ISTEL.2010.5734151 – ident: 10366_CR104 doi: 10.1145/3447548.3467404 – volume: 32 start-page: 1212 issue: 6 year: 2020 ident: 10366_CR64 publication-title: IEEE Trans Knowl Data Eng doi: 10.1109/TKDE.2019.2903410 – volume-title: Cluster analysis: a survey year: 2013 ident: 10366_CR37 – ident: 10366_CR176 doi: 10.1145/584792.584877 – ident: 10366_CR136 doi: 10.1145/361219.361220 – volume: 20 start-page: 871 issue: 8 year: 1998 ident: 10366_CR76 publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/34.709614 – volume-title: Finding groups in data: an introduction to cluster analysis year: 2009 ident: 10366_CR80 – volume: 163 start-page: 781 issue: 108 year: 2020 ident: 10366_CR24 publication-title: Stat Probab Lett doi: 10.1016/j.spl.2020.108781 – volume: 2 start-page: 165 issue: 2 year: 2015 ident: 10366_CR161 publication-title: Ann Data Sci doi: 10.1007/s40745-015-0040-1 – volume: 38 start-page: 47 issue: 1 year: 1973 ident: 10366_CR65 publication-title: Psychometrika doi: 10.1007/BF02291173 – ident: 10366_CR143 doi: 10.1086/408956 – volume: 21 start-page: 768 year: 1965 ident: 10366_CR43 publication-title: Biometrics – year: 2018 ident: 10366_CR179 publication-title: Complex doi: 10.1155/2018/2032461 – ident: 10366_CR12 – ident: 10366_CR159 doi: 10.1007/978-3-030-60796-8_37 – volume: 11 start-page: 583 issue: 6 year: 2007 ident: 10366_CR120 publication-title: Intell Data Anal doi: 10.3233/IDA-2007-11602 – ident: 10366_CR141 doi: 10.1109/COMPSAC.2018.00127 – ident: 10366_CR3 doi: 10.1109/CVPR.2005.89 – start-page: 25 volume-title: Grouping multidimensional data–recent advances in clustering year: 2006 ident: 10366_CR13 doi: 10.1007/3-540-28349-8_2 – ident: 10366_CR6 doi: 10.1109/ICDE48307.2020.00184 – volume: 42 start-page: 1791 issue: 7 year: 2020 ident: 10366_CR9 publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2019.2924953 – ident: 10366_CR170 doi: 10.1145/233269.233324 – volume: 2 start-page: 193 issue: 1 year: 1985 ident: 10366_CR66 publication-title: J Classif doi: 10.1007/BF01908075 – volume: 173 start-page: 3 year: 2016 ident: 10366_CR98 publication-title: Neurocomputing doi: 10.1016/j.neucom.2015.01.090 – volume: 14 start-page: 783 issue: 9 year: 1998 ident: 10366_CR53 publication-title: Bioinformatics doi: 10.1093/bioinformatics/14.9.783 – ident: 10366_CR52 – volume: 7 start-page: 69 issue: 1 year: 1999 ident: 10366_CR77 publication-title: IEEE Trans Very Large Scale Integr Syst doi: 10.1109/92.748202 – ident: 10366_CR105 doi: 10.1109/DEXA.2010.25 – volume: 2 start-page: 86 issue: 1 year: 2012 ident: 10366_CR109 publication-title: Wiley Interdiscip Rev Data Min Knowl Discov doi: 10.1002/widm.53 – ident: 10366_CR51 doi: 10.1109/CVPR.2005.50 – ident: 10366_CR173 – volume: 17 start-page: 611 issue: 5 year: 2002 ident: 10366_CR62 publication-title: J Comput Sci Technol doi: 10.1007/BF02948829 – volume: 30 start-page: 876 issue: 3 year: 2019 ident: 10366_CR31 publication-title: IEEE Trans Neural Netw Learn Syst doi: 10.1109/TNNLS.2018.2853407 – volume: 103 start-page: 102370 year: 2020 ident: 10366_CR68 publication-title: Omega doi: 10.1016/j.omega.2020.102370 – volume: 2 start-page: 651 issue: 4 year: 2007 ident: 10366_CR1 publication-title: Encycl Meas Stat – volume-title: Self-organizing maps, third edition. Springer series in information sciences year: 2001 ident: 10366_CR84 doi: 10.1007/978-3-642-56927-2 – year: 2017 ident: 10366_CR110 publication-title: Wiley Interdiscip Rev Data Min Knowl Discov doi: 10.1002/widm.1219 – volume: 12 start-page: 149 issue: 3 year: 2006 ident: 10366_CR25 publication-title: Int J Inf Technol – volume: 19 start-page: 2097 issue: 16 year: 2003 ident: 10366_CR124 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btg288 – ident: 10366_CR32 doi: 10.1109/ICCV.2009.5459322 – volume: 21 start-page: 450 issue: 5 year: 1999 ident: 10366_CR46 publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/34.765656 – volume: 204 start-page: 220 issue: 106 year: 2020 ident: 10366_CR131 publication-title: Knowl Based Syst doi: 10.1016/j.knosys.2020.106220 – volume: 1 start-page: 82 issue: 3 year: 2012 ident: 10366_CR142 publication-title: Int J Latest Trends Eng Technol – volume: 17 start-page: 107 issue: 2–3 year: 2001 ident: 10366_CR58 publication-title: J Intell Inf Syst doi: 10.1023/A:1012801612483 – volume: 45 start-page: 1669 issue: 8 year: 2015 ident: 10366_CR18 publication-title: IEEE Trans Cybern doi: 10.1109/TCYB.2014.2358564 – ident: 10366_CR47 doi: 10.1109/LA-CCI47412.2019.9036754 – volume: 37 start-page: 541 issue: 3 year: 2015 ident: 10366_CR95 publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2014.2346173 – volume: 128 start-page: 96 year: 2019 ident: 10366_CR130 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2019.03.031 – volume: 13 start-page: 10 issue: 1 year: 2019 ident: 10366_CR11 publication-title: ACM Trans Knowl Discov Data doi: 10.1145/3299876 – volume: 10 start-page: e0141756 issue: 10 year: 2015 ident: 10366_CR89 publication-title: PLoS ONE doi: 10.1371/journal.pone.0141756 – volume: 6 start-page: 1 issue: 2 year: 2020 ident: 10366_CR119 publication-title: Int J Interact Multim Artif Intell doi: 10.9781/ijimai.2020.03.001 – volume: 49 start-page: 1058 issue: 3 year: 2019 ident: 10366_CR61 publication-title: IEEE Trans Cybern doi: 10.1109/TCYB.2018.2794998 – volume: 16 start-page: 645 issue: 3 year: 2005 ident: 10366_CR162 publication-title: IEEE Trans Neural Netw doi: 10.1109/TNN.2005.845141 – ident: 10366_CR57 doi: 10.1109/ICMLC.2007.4370836 – ident: 10366_CR2 – ident: 10366_CR168 doi: 10.1109/FSKD.2009.205 – ident: 10366_CR54 doi: 10.1145/276304.276312 – volume: 32 start-page: 241 issue: 3 year: 1967 ident: 10366_CR75 publication-title: Psychometrika doi: 10.1007/BF02289588 – volume: 25 start-page: 345 issue: 5 year: 2000 ident: 10366_CR55 publication-title: Inf Syst doi: 10.1016/S0306-4379(00)00022-3 – ident: 10366_CR156 – volume: 17 start-page: 395 issue: 4 year: 2007 ident: 10366_CR99 publication-title: Stat Comput doi: 10.1007/s11222-007-9033-z – ident: 10366_CR153 – ident: 10366_CR175 doi: 10.1109/IJCNN48605.2020.9206722 – ident: 10366_CR146 doi: 10.1109/GrC.2012.6468689 – volume: 35 start-page: 345 issue: 2 year: 2018 ident: 10366_CR132 publication-title: J Classif doi: 10.1007/s00357-018-9259-9 – start-page: 87 volume-title: Data clustering: algorithms and applications year: 2013 ident: 10366_CR127 – ident: 10366_CR116 doi: 10.1109/UPCON.2018.8596795 – volume: 10 start-page: 1591 issue: 7 year: 2019 ident: 10366_CR27 publication-title: Int J Mach Learn Cybern doi: 10.1007/s13042-018-0836-3 – volume: 24 start-page: 95 issue: 2 year: 1996 ident: 10366_CR23 publication-title: Mach Learn doi: 10.1007/BF00058654 – volume: 99 start-page: 7821 issue: 12 year: 2002 ident: 10366_CR49 publication-title: Proc Natl Acad Sci USA doi: 10.1073/pnas.122653799 – volume: 120 start-page: 584 issue: 108 year: 2022 ident: 10366_CR154 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2022.108584 – volume: 123 start-page: 10 year: 2019 ident: 10366_CR164 publication-title: Comput Geosci doi: 10.1016/j.cageo.2018.11.003 – ident: 10366_CR125 doi: 10.1109/ICIP.2014.7025983 – volume: 21 start-page: 120 issue: 1 year: 2020 ident: 10366_CR67 publication-title: BMC Bioinform doi: 10.1186/s12859-020-3453-6 – ident: 10366_CR149 doi: 10.1109/RAICS.2011.6069433 – volume: 35 start-page: 407 issue: 100 year: 2020 ident: 10366_CR38 publication-title: Spat Stat doi: 10.1016/j.spasta.2020.100407 – ident: 10366_CR56 doi: 10.1109/ICDM.2008.115 – volume: 35 start-page: 21 issue: C year: 2012 ident: 10366_CR7 publication-title: Neural Netw doi: 10.1016/j.neunet.2012.06.007 – volume: 26 start-page: 195 issue: 2 year: 1984 ident: 10366_CR128 publication-title: SIAM Rev doi: 10.1137/1026034 – volume: 25 start-page: 023107 issue: 2 year: 2015 ident: 10366_CR166 publication-title: Chaos doi: 10.1063/1.4908014 – volume: 22 start-page: 151 issue: 2 year: 2005 ident: 10366_CR145 publication-title: J Classif doi: 10.1007/s00357-005-0012-9 – volume: 7 start-page: 421 issue: 1 year: 2020 ident: 10366_CR19 publication-title: IEEE Trans Netw Sci Eng doi: 10.1109/TNSE.2018.2830822 – volume: 1 start-page: 7 issue: 1 year: 1984 ident: 10366_CR34 publication-title: J Classif doi: 10.1007/BF01890115 – ident: 10366_CR60 doi: 10.1145/3534678.3539323 – ident: 10366_CR178 doi: 10.7551/mitpress/7503.003.0205 – ident: 10366_CR126 doi: 10.1109/IC4ME2.2018.8465616 – volume: 2 start-page: 325 issue: 4 year: 1998 ident: 10366_CR14 publication-title: Data Min Knowl Disc doi: 10.1023/A:1009740529316 – volume: 202 start-page: 1034 issue: 4936 year: 1964 ident: 10366_CR101 publication-title: Nature doi: 10.1038/2021034a0 – ident: 10366_CR22 doi: 10.1145/3195106.3195118 – volume-title: Algorithms for clustering data year: 1988 ident: 10366_CR69 – ident: 10366_CR10 doi: 10.1109/ICDMW.2016.0123 – ident: 10366_CR48 doi: 10.1109/CSBW.2005.10 – volume: 26 start-page: 354 issue: 4 year: 1983 ident: 10366_CR108 publication-title: Comput J doi: 10.1093/comjnl/26.4.354 – volume-title: Finding groups in data: an introduction to cluster analysis year: 1990 ident: 10366_CR79 doi: 10.1002/9780470316801 – volume: 49 start-page: 291 issue: 2 year: 1970 ident: 10366_CR82 publication-title: Bell Syst Tech J doi: 10.1002/j.1538-7305.1970.tb01770.x – volume: 68 start-page: 542 issue: 4 year: 2019 ident: 10366_CR121 publication-title: IEEE Trans Comput doi: 10.1109/TC.2018.2879332 – volume: 25 start-page: 165 year: 1969 ident: 10366_CR158 publication-title: Biometrics doi: 10.2307/2528688 – volume: 20 start-page: 68 issue: 1 year: 1971 ident: 10366_CR167 publication-title: IEEE Trans Comput doi: 10.1109/T-C.1971.223083 – volume: 103 start-page: 101871 issue: C year: 2022 ident: 10366_CR180 publication-title: Inf Syst doi: 10.1016/j.is.2021.101871 – ident: 10366_CR106 doi: 10.1109/NoF50125.2020.9249194 – volume: 171 start-page: 32 year: 2020 ident: 10366_CR134 publication-title: Procedia Comput Sci doi: 10.1016/j.procs.2020.04.004 – volume: 2 start-page: 314 issue: 3 year: 2011 ident: 10366_CR150 publication-title: Adv Appl Sci Res – ident: 10366_CR102 doi: 10.1109/ICDM.2015.90 – volume: 13 start-page: 2983 issue: 6 year: 2022 ident: 10366_CR118 publication-title: J Ambient Intell Humaniz Comput doi: 10.1007/s12652-021-03673-0 – ident: 10366_CR165 doi: 10.1109/GrC.2007.34 – volume: 42 start-page: 2785 issue: 5 year: 2015 ident: 10366_CR15 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2014.09.054 – ident: 10366_CR29 doi: 10.1109/WI-IAT.2012.9 – volume: 28 start-page: 623 issue: 6 year: 1980 ident: 10366_CR112 publication-title: IEEE Trans Acoust Speech Signal Process doi: 10.1109/TASSP.1980.1163491 – ident: 10366_CR138 doi: 10.1109/CIBCB.2018.8404978 – volume-title: Introduction to data mining year: 2019 ident: 10366_CR147 – volume: 9 start-page: 373 issue: 4 year: 1967 ident: 10366_CR88 publication-title: Comput J doi: 10.1093/comjnl/9.4.373 – volume: 67 start-page: 401 year: 2014 ident: 10366_CR123 publication-title: Knowl Based Syst doi: 10.1016/j.knosys.2014.03.013 – volume: 24 start-page: 228 issue: 2 year: 1986 ident: 10366_CR17 publication-title: Eur J Oper Res doi: 10.1016/0377-2217(86)90044-5 – volume-title: Cluster analysis year: 2001 ident: 10366_CR41 – volume: 1 start-page: 73 issue: 1 year: 2004 ident: 10366_CR85 publication-title: WSEAS Trans Inf Sci Appl – ident: 10366_CR144 – ident: 10366_CR163 doi: 10.1109/CcS49175.2020.9231474 – volume: 33 start-page: 3075 issue: 8 year: 2021 ident: 10366_CR117 publication-title: IEEE Trans Knowl Data Eng doi: 10.1109/TKDE.2019.2962412 – volume: 78 start-page: 1494 issue: 9 year: 2008 ident: 10366_CR152 publication-title: Electr Power Syst Res doi: 10.1016/j.epsr.2008.01.010 – volume: 39 start-page: e95 issue: 14 year: 2011 ident: 10366_CR20 publication-title: Nucleic Acids Res doi: 10.1093/nar/gkr349 – ident: 10366_CR87 – volume-title: ACTORS—a model of concurrent computation in distributed systems. MIT Press series in artificial intelligence year: 1990 ident: 10366_CR4 – ident: 10366_CR174 doi: 10.1109/WKDD.2010.123 – volume-title: Matrix computations year: 1996 ident: 10366_CR50 – ident: 10366_CR155 – ident: 10366_CR83 doi: 10.1145/3097983.3098079 – volume-title: The Sage encyclopedia of social science research methods year: 2003 ident: 10366_CR90 – volume: 46 start-page: 1227 issue: 5 year: 2013 ident: 10366_CR97 publication-title: Pattern Recognit doi: 10.1016/j.patcog.2012.11.017 – ident: 10366_CR107 – volume: 5 start-page: 83 issue: 4 year: 2011 ident: 10366_CR59 publication-title: Morgan Kaufmann Ser Data Manag Syst – ident: 10366_CR157 doi: 10.1007/978-3-319-63315-2_28 – volume: 39 start-page: 1853 issue: 9 year: 2017 ident: 10366_CR33 publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/TPAMI.2016.2615921 – volume: 26 start-page: 2534 issue: 9 year: 2015 ident: 10366_CR74 publication-title: IEEE Trans Parallel Distrib Syst doi: 10.1109/TPDS.2014.2355205
SSID	ssj0005243
Score	2.6681736
Snippet	Data clustering is a commonly used data processing technique in many fields, which divides objects into different clusters in terms of some similarity measure...
SourceID	proquest gale crossref springer
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	8219
SubjectTerms	Algorithms Artificial Intelligence Cluster analysis Clustering Computer Science Data points Data processing Deep learning Hierarchies Partition Production methods Similarity Similarity measures Surveys
SummonAdditionalLinks	– databaseName: SpringerLINK dbid: RSV link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnR3JSgMxNGj14MW6YrVKDoIHHehMMpPJsYjFUxGX0lvINlaoU5lpC_69L7PYuoJeJ5mX8F7extsQOqVRQGOtwTfxA-bRRFKPq9jlTEWBUlEgOVXFsAnW78fDIb-pisLyOtu9DkkWknqp2A0Aey773AexG3lkFa2BuosdO97eDZYSO8pcuSDiHjgUflUq8z2MD-ros1D-Eh0tlE6v-b_rbqHNysjE3fJVbKMVm-6gZj3AAVf8vIsG7lNmR2USO85n2dy-4kmK3YDsIsQAFMR6PHPdFOBwLMePk-xpOnrOsUwNBuMRg8QEvYXNIvko30MPvav7y2uvGrTgaRLGUy9MDPhZgTG8ow2VkQ6lH4VuWlXCk440obGJ9TmzxLeuvzxRkpgOVyYgOiK2Q_ZRI52k9gBhy5QNk0ADoJhKwmRCQuVzsPOYoUyxFvJrfAtddSF3wzDGYtE_2SFOAOJEgThBWuj8_Z-XsgfHr7vPHBmFY1CArGVVZwD3c62uRJeBSwwqmsBd2jWlRcW5uXCRZTDRKIXli5qyi-Wfzz382_YjtOEm15e5hG3UmGYze4zW9Xz6lGcnxYt-A4zE7v8 priority: 102 providerName: Springer Nature
Title	Comprehensive survey on hierarchical clustering algorithms and the recent developments
URI	https://link.springer.com/article/10.1007/s10462-022-10366-3 https://www.proquest.com/docview/2829976447
Volume	56
WOSCitedRecordID	wos000903993600003&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 1573-7462 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0005243 issn: 0269-2821 databaseCode: RSV dateStart: 19970101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwELZoy4FLy1MslJUPSBzAIn4kjk-oVK2QEMuqQClcLMd2aKUlWza7lfj3zCQOC63ohcscktgeZcYztmc8HyFPVSFU6T3sTbjQTNVOMVOVmDNViKoqhDOq6sAm9GRSnpyYaTpwa1Na5WATO0Md5h7PyF9ixA9cp1L61fkPhqhRGF1NEBobZIsLwVHP32r2R4pHnzUnCsOgPU-XZtLVOWCTYS47ByNeMPmXY7psnq_ESTv3c7jzv4zfJttp4Un3ek25Q27E5i7ZGUAdaJrj98gxPlrE0z6xnbarxUX8SecNRdDsLuwAUqV-tsIKC8AqdbNvMNzy9HtLXRMoLCgpWFHwZTSsE5La--TT4cHH_TcsgS8wL_NyyfI6wN5LhGAyH5QrfO54kSOCVW3qzIU8xDpyo6PkEWvOy8rJkJkqCOkLGTP5gGw28yY-JDTqKua18NBRqZzUrpZ5xQ2s_XRQutIjwoc_b32qTI4AGTO7rqmM0rIgLdtJy8oRef67zXlfl-Par5-hQC1OWujZu3T3APjD8ld2T8M2Gdy2BF52BynaNJtbuxbhiLwY9GD9-t_jPrq-t8fkFqLX9_mEu2RzuVjFJ-Smv1ietYsx2dCfv4zJ1uuDyfRo3Gk20HfZPlL-Hug0_wr06MPxL1Vm_4w
linkProvider	ProQuest
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB6VgkQvlKdYKOADiANETWwnjg8IVYWqVcuKQ0G9Gb9CkbbZstkt6p_iNzKTB8tD9NYD1zwmfnyesTPfzAA8lQWXpfd4Nsm4SmRlZaJdSZypgjtXcKula4tNqPG4PDrS71fg-xALQ7TKQSe2ijpMPf0j3ySPH5pOKdXr068JVY0i7-pQQqODxX48_4ZHtubV3huc32ec77w93N5N-qoCiRd5OU_yKuChgoegUx-kLXxusyKn0kyVrlIb8hCrmGkVRRYpmbpwVoRUu8CFL0RMBcq9AlelxOVAVMF0-xdKScfS44VOsL1ZH6TTh-rhsCTEnc_QaBSJ-M0Q_mkO_vLLtuZuZ_1_G6ibcKPfWLOtbiXcgpVY34b1oWgF63XYHfhIl2bxuCPus2YxO4vnbFozKgreulUQtcxPFpRBAoeG2cln7N78-KRhtg4MN8wMrQTaahaWhKvmLny4lN7dg9V6Wsf7wKJyMa-4R0GltELZSuQu07i3VUEqp0aQDTNtfJ95nQqATMwyZzShwyA6TIsOI0bw4uc7p13ekQuffk4AMqSUULK3fWwFto_Se5ktlWMfVCmwLRsDakyvrRqzhMwIXg64W97-93cfXCztCVzfPXx3YA72xvsPYY3j_rDjTm7A6ny2iI_gmj-bf2lmj9t1xODTZePxB5gAVto
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Jb9QwFH4qBSEulFUMtOADiANEnXiJ40NVVZQRVdFoDoAqLsZbKNKQKZOZov41fl2fE4dhEb31wDWL4-XzW-LvvQfwlBeUl86hb5JTmfHK8EzZMnKmCmptQY3iti02Icfj8uhITdbgRx8LE2mVvUxsBbWfufiPfDue-KHq5FxuV4kWMdkf7Z58y2IFqXjS2pfT6CByGM6-o_vW7Bzs41o_o3T0-t2rN1mqMJA5JspFJiqPDgb1Xg2d56ZwwuSFiGWaKlUNjRc-VCFXMrA8xMTqzBrmh8p6ylzBwpBhu1fgqkQfMzp-E_HxF3pJx9ijhcqw73kK2ElhezhFWeTR56hAioz9phT_VA1_ndG2qm-08T9P2i24mQxustftkNuwFuo7sNEXsyBJtt2FD_HSPBx3hH7SLOen4YzMahKLhbfHLYhm4qbLmFkCp4mY6Wcc3uL4a0NM7Qka0gS1B-pw4ldErOYevL-U0d2H9XpWhwdAgrRBVNRhQyU3TJqKCZsrtHml59LKAeT9qmuXMrLHwiBTvcolHZGiESm6RYpmA3jx852TLh_JhU8_j2DSUVhhy86kmAvsX0z7pfekwDHIkmFfNnsE6STFGr2CzwBe9hhc3f73dx9e3NoTuI4w1G8PxoeP4AZFs7GjVG7C-mK-DFtwzZ0uvjTzx-2WIvDpsuF4DgBxX-s
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Comprehensive+survey+on+hierarchical+clustering+algorithms+and+the+recent+developments&rft.jtitle=The+Artificial+intelligence+review&rft.date=2023-08-01&rft.pub=Springer+Nature+B.V&rft.issn=0269-2821&rft.eissn=1573-7462&rft.volume=56&rft.issue=8&rft.spage=8219&rft.epage=8264&rft_id=info:doi/10.1007%2Fs10462-022-10366-3&rft.externalDBID=HAS_PDF_LINK
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0269-2821&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0269-2821&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0269-2821&client=summon