Optimal scale selection approach for classification based on generalized multi-scale formal context
The classification of multi-scale data is an important research topic in granular computing. Its research goal is to determine the most appropriate scale and achieve better classification performance. However, determining the optimal scale is often a difficult problem due to lacking better metrics a...
Uloženo v:
| Vydáno v: | Applied soft computing Ročník 152; s. 111277 |
|---|---|
| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
01.02.2024
|
| Témata: | |
| ISSN: | 1568-4946 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | The classification of multi-scale data is an important research topic in granular computing. Its research goal is to determine the most appropriate scale and achieve better classification performance. However, determining the optimal scale is often a difficult problem due to lacking better metrics and optimization methods. In order to solve this problem, this paper proposes the optimal scale selection criteria for generalized multi-scale formal contexts. That is, the optimal scale uses the coarsest conditional attributes and finest decision attributes to optimize the combination of granularities of attributes. We combine these criteria with multi-objective optimization methods for developing an algorithm to fast compute the optimal scale. Experiments show that for the selected 14 data sets and 11 comparative classification methods, there are 9 classification methods with higher classification accuracies on more than 9 data sets. Therefore, the optimal scale selection method proposed in this paper is feasible and can effectively improve the performance of the classification method.
•We propose a generalized multi-scale formal context with multi-scale conditional and decision attributes.•We define the optimal scale with the coarsest conditional attribute and finest decision attribute.•Criteria are given to the optimal scale selection in generalized multi-scale formal contexts.•We use optimization method to explore an algorithm for computing the optimal scale.•Datasets are chosen to show the effectiveness of the proposed methods. |
|---|---|
| AbstractList | The classification of multi-scale data is an important research topic in granular computing. Its research goal is to determine the most appropriate scale and achieve better classification performance. However, determining the optimal scale is often a difficult problem due to lacking better metrics and optimization methods. In order to solve this problem, this paper proposes the optimal scale selection criteria for generalized multi-scale formal contexts. That is, the optimal scale uses the coarsest conditional attributes and finest decision attributes to optimize the combination of granularities of attributes. We combine these criteria with multi-objective optimization methods for developing an algorithm to fast compute the optimal scale. Experiments show that for the selected 14 data sets and 11 comparative classification methods, there are 9 classification methods with higher classification accuracies on more than 9 data sets. Therefore, the optimal scale selection method proposed in this paper is feasible and can effectively improve the performance of the classification method.
•We propose a generalized multi-scale formal context with multi-scale conditional and decision attributes.•We define the optimal scale with the coarsest conditional attribute and finest decision attribute.•Criteria are given to the optimal scale selection in generalized multi-scale formal contexts.•We use optimization method to explore an algorithm for computing the optimal scale.•Datasets are chosen to show the effectiveness of the proposed methods. |
| ArticleNumber | 111277 |
| Author | Yu, Chongchong Li, Jinhai Wang, Fei |
| Author_xml | – sequence: 1 givenname: Fei surname: Wang fullname: Wang, Fei email: wangfei971023@163.com organization: Faculty of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, PR China – sequence: 2 givenname: Jinhai orcidid: 0000-0002-5206-9304 surname: Li fullname: Li, Jinhai email: jhlixjtu@163.com organization: Faculty of Science, Kunming University of Science and Technology, Yunnan 650500, PR China – sequence: 3 givenname: Chongchong surname: Yu fullname: Yu, Chongchong email: chongzhy@vip.sina.com organization: Faculty of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, PR China |
| BookMark | eNp9kMtOwzAQRb0oEm3hB1jlBxLsxHlJbFDFS6rUTffWZGyDKzeObIOAr8clrFh0NR6Nz5XuWZHF6EZFyA2jBaOsuT0UEBwWJS15wRgr23ZBlqxuupz3vLkkqxAONH3sy25JcDdFcwSbBQSrsqCswmjcmME0eQf4lmnnM7QQgtEG4fc2QFAyS49XNSoP1nyn9fhuo8nnmMScMtGNUX3GK3KhwQZ1_TfXZP_4sN8859vd08vmfptjRWnMG-wV58BkLQeu604j6q7DSg8D5TVt2gq4hpZWrJeo-r7jKKFFpBqglLxak3KORe9C8EqLyadq_kswKk5mxEGczIiTGTGbSVD3D0ITf1tGD8aeR-9mVKVOH0Z5EdCoEZU0PkkU0plz-A9ZdoZ6 |
| CitedBy_id | crossref_primary_10_1016_j_knosys_2025_113552 crossref_primary_10_1016_j_ijar_2025_109429 crossref_primary_10_1016_j_asoc_2025_112712 crossref_primary_10_1016_j_inffus_2024_102775 |
| Cites_doi | 10.1016/j.ijar.2022.12.004 10.1016/j.ins.2021.10.065 10.1109/TFUZZ.2021.3128061 10.1016/j.ins.2020.05.109 10.1016/j.ijar.2023.108983 10.1016/j.knosys.2015.08.006 10.1016/j.ins.2015.12.028 10.1016/j.ins.2014.12.010 10.1007/s13042-020-01243-y 10.1016/j.ins.2012.10.030 10.1109/TKDE.2008.223 10.1016/S0020-0255(03)00061-6 10.1109/TNNLS.2021.3054063 10.1016/j.ijar.2019.11.002 10.1016/j.ins.2016.01.091 10.1016/j.inffus.2023.101962 10.1016/j.ins.2016.03.041 10.1016/j.knosys.2016.04.011 10.1007/s13042-020-01173-9 10.1016/j.ijar.2018.09.005 10.1016/j.ins.2023.118998 10.1016/j.ijar.2012.07.005 10.1016/j.ins.2013.10.021 10.1109/TSMCB.2009.2013334 10.1016/j.ins.2011.04.047 10.1016/j.ins.2016.04.051 10.1007/s13042-012-0128-2 10.1016/j.ins.2009.11.023 10.1007/s13042-018-0803-z 10.1109/TFUZZ.2022.3216110 10.1016/j.ins.2019.05.009 10.1016/j.fss.2017.05.002 10.1007/s12652-020-01867-6 10.1016/j.ijar.2019.09.010 10.1007/s13042-019-00954-1 10.1007/s13042-016-0553-8 10.1016/j.ins.2013.12.014 10.1007/s12652-018-0831-2 10.1002/1098-111X(200101)16:1<87::AID-INT7>3.0.CO;2-S 10.1007/s13042-020-01101-x 10.1007/s13042-019-01015-3 10.1093/logcom/10.6.823 |
| ContentType | Journal Article |
| Copyright | 2024 Elsevier B.V. |
| Copyright_xml | – notice: 2024 Elsevier B.V. |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.asoc.2024.111277 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| ExternalDocumentID | 10_1016_j_asoc_2024_111277 S1568494624000516 |
| GroupedDBID | --K --M .DC .~1 0R~ 1B1 1~. 1~5 23M 4.4 457 4G. 53G 5GY 5VS 6J9 7-5 71M 8P~ AABNK AACTN AAEDT AAEDW AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AAXKI AAXUO AAYFN ABBOA ABFNM ABFRF ABJNI ABMAC ABWVN ABXDB ACDAQ ACGFO ACGFS ACNNM ACRLP ACRPL ACZNC ADBBV ADEZE ADJOM ADMUD ADNMO ADTZH AEBSH AECPX AEFWE AEIPS AEKER AENEX AFJKZ AFKWA AFTJW AGHFR AGUBO AGYEJ AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJOXV AKRWK ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ ANKPU AOUOD ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BLXMC CS3 EBS EFJIC EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HVGLF HZ~ IHE J1W JJJVA KOM M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SDF SDG SES SEW SPC SPCBC SST SSV SSZ T5K UHS UNMZH ~G- 9DU AATTM AAYWO AAYXX ACLOT ACVFH ADCNI AEUPX AFPUW AGQPQ AIGII AIIUN AKBMS AKYEP APXCP CITATION EFKBS EFLBG ~HD |
| ID | FETCH-LOGICAL-c300t-6c9e44a1d5db4f58fccf88c3fbb0450673a4fa70319dce9984cda7cc0faa2d43 |
| ISICitedReferencesCount | 5 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001166171700001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1568-4946 |
| IngestDate | Tue Nov 18 21:57:21 EST 2025 Sat Nov 29 08:10:27 EST 2025 Sat Feb 08 15:52:15 EST 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Generalized multi-scale formal context Multi-objective optimization methods Optimal scale selection criteria Classification |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c300t-6c9e44a1d5db4f58fccf88c3fbb0450673a4fa70319dce9984cda7cc0faa2d43 |
| ORCID | 0000-0002-5206-9304 |
| ParticipantIDs | crossref_primary_10_1016_j_asoc_2024_111277 crossref_citationtrail_10_1016_j_asoc_2024_111277 elsevier_sciencedirect_doi_10_1016_j_asoc_2024_111277 |
| PublicationCentury | 2000 |
| PublicationDate | February 2024 2024-02-00 |
| PublicationDateYYYYMMDD | 2024-02-01 |
| PublicationDate_xml | – month: 02 year: 2024 text: February 2024 |
| PublicationDecade | 2020 |
| PublicationTitle | Applied soft computing |
| PublicationYear | 2024 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Zhang (b19) 2018; 333 Li, Huang, Qi, Qian, Liu (b22) 2017; 378 Yao (b36) 2018; 103 Wu, Leung (b40) 2020; 11 Shao, Li, Wang (b29) 2018; 9 Niu, Chen, Li, Wang (b50) 2021; 30 Chen, Xu, Li, Hu (b9) 2019 Qian, Li, Liang, Shi, Wang (b42) 2014; 264 Belohlávek (b2) 2000; 10 Yang, Qin, Hu, Yang (b7) 2023; 53 Bao, Wu, Zheng, Li (b41) 2021; 12 Zhang, Huang (b47) 2023; 161 Lin (b34) 1998; 1 Guo, Xu (b53) 2023; 639 Xie, Liu (b14) 2002; 25 Zhao, Li, Liu, Xu (b27) 2017; 8 Medina (b6) 2013; 225 Yao (b37) 2020; 116 Zhang, Cheng, Zhao, Wang, Xia (b46) 2021; 33 Xu, Guo, Qian, Ding (b55) 2023; 31 Zhi, Li (b23) 2016; 104 Yao (b24) 2016; 346/347 Shi, Mi, Li, Liu (b49) 2019; 496 Qian, Liang, Yao, Dang (b38) 2010; 180 Chen, Li, Lin (b32) 2020; 11 Cheng, Zhang, Wang (b44) 2021; 12 Zhai, Wang, Li (b8) 2023 Cheng, Zhang, Wang, Hu (b45) 2020; 541 Huang, Li, Dai, Lin (b11) 2019; 115 Shao, Yang (b30) 2013; 4 Wu, Leung (b15) 2011; 181 Yao (b25) 2009; 39 She, He, Qian, Wang, Zeng (b31) 2019; 10 Niu, Chen, Li, Wang (b51) 2022; 584 Zadeh (b33) 1979 Qi, Wei, Yao (b21) 2014; vol. 8818 Guo, Xu, Qian, Ding (b54) 2023 Pedrycz (b10) 2001 Zhang, Zhang, Cheng, Wang (b43) 2020; 11 Wu, Qian, Li, Gu (b13) 2017; 378 Wu, Niu, Li, Li (b12) 2023; 154 Li, Mei, Lv (b16) 2013; 54 Guo, Xu, Qian, Ding (b52) 2023; 100 Wu, Leung, Mi (b39) 2009; 21 Düntsch, Gediga (b17) 2000 Ganter, Wille (b1) 1999 Xu, Li, Wei, Zhang (b18) 2016 Qi, Qian, Wei (b4) 2016; 91 Yao, Han, Wang (b5) 2016; 339 Yao (b35) 2001; 16 Sumangali, Kumar (b3) 2019; 10 Shao, Zhang (b20) 1979 Belohlávek, Baets, Konecny (b28) 2014; 260 Li, Mei, Xu, Qian (b26) 2015; 298 Leung, Li (b48) 2003; 153 Li (10.1016/j.asoc.2024.111277_b16) 2013; 54 Yao (10.1016/j.asoc.2024.111277_b24) 2016; 346/347 Chen (10.1016/j.asoc.2024.111277_b9) 2019 Qian (10.1016/j.asoc.2024.111277_b42) 2014; 264 She (10.1016/j.asoc.2024.111277_b31) 2019; 10 Lin (10.1016/j.asoc.2024.111277_b34) 1998; 1 Pedrycz (10.1016/j.asoc.2024.111277_b10) 2001 Yao (10.1016/j.asoc.2024.111277_b36) 2018; 103 Belohlávek (10.1016/j.asoc.2024.111277_b28) 2014; 260 Li (10.1016/j.asoc.2024.111277_b22) 2017; 378 Zhao (10.1016/j.asoc.2024.111277_b27) 2017; 8 Zhai (10.1016/j.asoc.2024.111277_b8) 2023 Wu (10.1016/j.asoc.2024.111277_b15) 2011; 181 Yao (10.1016/j.asoc.2024.111277_b35) 2001; 16 Chen (10.1016/j.asoc.2024.111277_b32) 2020; 11 Niu (10.1016/j.asoc.2024.111277_b50) 2021; 30 Yang (10.1016/j.asoc.2024.111277_b7) 2023; 53 Xie (10.1016/j.asoc.2024.111277_b14) 2002; 25 Zhang (10.1016/j.asoc.2024.111277_b19) 2018; 333 Belohlávek (10.1016/j.asoc.2024.111277_b2) 2000; 10 Zhang (10.1016/j.asoc.2024.111277_b43) 2020; 11 Cheng (10.1016/j.asoc.2024.111277_b44) 2021; 12 Ganter (10.1016/j.asoc.2024.111277_b1) 1999 Niu (10.1016/j.asoc.2024.111277_b51) 2022; 584 Yao (10.1016/j.asoc.2024.111277_b37) 2020; 116 Shao (10.1016/j.asoc.2024.111277_b30) 2013; 4 Qi (10.1016/j.asoc.2024.111277_b4) 2016; 91 Cheng (10.1016/j.asoc.2024.111277_b45) 2020; 541 Qian (10.1016/j.asoc.2024.111277_b38) 2010; 180 Qi (10.1016/j.asoc.2024.111277_b21) 2014; vol. 8818 Bao (10.1016/j.asoc.2024.111277_b41) 2021; 12 Wu (10.1016/j.asoc.2024.111277_b39) 2009; 21 Guo (10.1016/j.asoc.2024.111277_b52) 2023; 100 Sumangali (10.1016/j.asoc.2024.111277_b3) 2019; 10 Yao (10.1016/j.asoc.2024.111277_b25) 2009; 39 Yao (10.1016/j.asoc.2024.111277_b5) 2016; 339 Düntsch (10.1016/j.asoc.2024.111277_b17) 2000 Guo (10.1016/j.asoc.2024.111277_b54) 2023 Xu (10.1016/j.asoc.2024.111277_b18) 2016 Zhi (10.1016/j.asoc.2024.111277_b23) 2016; 104 Shao (10.1016/j.asoc.2024.111277_b29) 2018; 9 Medina (10.1016/j.asoc.2024.111277_b6) 2013; 225 Huang (10.1016/j.asoc.2024.111277_b11) 2019; 115 Zadeh (10.1016/j.asoc.2024.111277_b33) 1979 Wu (10.1016/j.asoc.2024.111277_b13) 2017; 378 Zhang (10.1016/j.asoc.2024.111277_b47) 2023; 161 Xu (10.1016/j.asoc.2024.111277_b55) 2023; 31 Guo (10.1016/j.asoc.2024.111277_b53) 2023; 639 Wu (10.1016/j.asoc.2024.111277_b12) 2023; 154 Wu (10.1016/j.asoc.2024.111277_b40) 2020; 11 Leung (10.1016/j.asoc.2024.111277_b48) 2003; 153 Li (10.1016/j.asoc.2024.111277_b26) 2015; 298 Shao (10.1016/j.asoc.2024.111277_b20) 1979 Zhang (10.1016/j.asoc.2024.111277_b46) 2021; 33 Shi (10.1016/j.asoc.2024.111277_b49) 2019; 496 |
| References_xml | – volume: 298 start-page: 447 year: 2015 end-page: 467 ident: b26 article-title: Concept learning via granular computing: A cognitive viewpoint publication-title: Inform. Sci. – volume: 180 start-page: 949 year: 2010 end-page: 970 ident: b38 article-title: MGRS: A multi-granulation rough set publication-title: Inform. Sci. – start-page: 1349 year: 2001 end-page: 1354 ident: b10 article-title: Granular computing: [a]n introduction publication-title: Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference, Vancouver, Canada, Vol. 3 – volume: 154 start-page: 56 year: 2023 end-page: 71 ident: b12 article-title: Rule acquisition in generalized multi-scale information systems with multi-scale decisions publication-title: Internat. J. Approx. Reason. – volume: 11 start-page: 961 year: 2020 end-page: 972 ident: b40 article-title: A comparison study of optimal scale combination selection in generalized multi-scale decision tables publication-title: Int. J. Mach. Learn. Cybern. – volume: 378 start-page: 244 year: 2017 end-page: 263 ident: b22 article-title: Three-way cognitive concept learning via multi-granularity publication-title: Inform. Sci. – volume: 16 start-page: 87 year: 2001 end-page: 104 ident: b35 article-title: Information granulation and rough set approximation publication-title: Int. J. Intell. Syst. – volume: 115 start-page: 194 year: 2019 end-page: 208 ident: b11 article-title: Generalized multi-scale decision tables with multi-scale decision attributes publication-title: Internat. J. Approx. Reason. – volume: 264 start-page: 196 year: 2014 end-page: 210 ident: b42 article-title: Pessimistic rough set based decisions: A multi-granulation fusion strategy publication-title: Inform. Sci. – volume: 11 start-page: 1095 year: 2020 end-page: 1114 ident: b43 article-title: Optimal scale selection by integrating uncertainty and cost-sensitive learning in multi-scale decision tables publication-title: Int. J. Mach. Learn. Cybern. – volume: 25 start-page: 490 year: 2002 end-page: 496 ident: b14 article-title: Fast asymptotic construction algorithm for concept lattice publication-title: J. Comput. Sci. – year: 2023 ident: b54 article-title: Fuzzy-granular concept-cognitive learning via three-way decision: Performance evaluation on dynamic knowledge discovery publication-title: IEEE Trans. Fuzzy Syst. – start-page: 281 year: 2000 end-page: 301 ident: b17 article-title: Rough set data analysis publication-title: Encyclopedia of Computer Science and Technology, Vol. 43, no. 28 – volume: vol. 8818 start-page: 732 year: 2014 end-page: 741 ident: b21 article-title: Three-way formal concept analysis publication-title: Lecture Notes in Artificial Intelligence – volume: 260 start-page: 149 year: 2014 end-page: 170 ident: b28 article-title: Granularity of attributes in formal concept analysis publication-title: Inform. Sci. – year: 1999 ident: b1 article-title: Formal concept analysis publication-title: Mathematical Foundations – volume: 53 start-page: 6025 year: 2023 end-page: 6040 ident: b7 article-title: Neighborhood based concept lattice publication-title: Appl. Intell. – volume: 54 start-page: 149 year: 2013 end-page: 165 ident: b16 article-title: Incomplete decision contexts: Approximate concept construction, rule acquisition and knowledge reduction publication-title: Int. J. Approx. Reason. – volume: 339 start-page: 1 year: 2016 end-page: 18 ident: b5 article-title: Lattice-theoretic contexts and their concept lattices via Galois ideals publication-title: Inform. Sci. – volume: 21 start-page: 1461 year: 2009 end-page: 1474 ident: b39 article-title: Granular computing and knowledge reduction in formal contexts publication-title: IEEE Trans. Knowl. Data Eng. – volume: 11 start-page: 5315 year: 2020 end-page: 5327 ident: b32 article-title: Formal concept analysis of multi-scale formal context publication-title: J. Ambient Intell. Humaniz. Comput. – volume: 1 start-page: 107 year: 1998 end-page: 121 ident: b34 article-title: Granular computing on binary relations I: Data mining and neighborhood systems publication-title: Rough Sets Konwl. Discov. – volume: 639 year: 2023 ident: b53 article-title: Fuzzy-based concept-cognitive learning: An investigation of novel approach to tumor diagnosis analysis publication-title: Inform. Sci. – volume: 10 start-page: 2327 year: 2019 end-page: 2343 ident: b3 article-title: Concept lattice simplification in formal concept analysis using attribute clustering publication-title: J. Ambient Intell. Humaniz. Comput. – volume: 181 start-page: 3878 year: 2011 end-page: 3897 ident: b15 article-title: Theory and applications of granular labelled partitions in multi-scale decision tables publication-title: Inform. Sci. – volume: 10 start-page: 823 year: 2000 end-page: 845 ident: b2 article-title: Similarity relations in concept lattices publication-title: J. Logic Comput. – volume: 378 start-page: 282 year: 2017 end-page: 302 ident: b13 article-title: On rule acquisition in incomplete multi-scale decision tables publication-title: Inform. Sci. – volume: 30 start-page: 3748 year: 2021 end-page: 3761 ident: b50 article-title: Fuzzy rule-based classification method for incremental rule learning publication-title: IEEE Trans. Fuzzy Syst. – volume: 9 start-page: 1869 year: 2018 end-page: 1877 ident: b29 article-title: Connections between two-universe rough sets and formal concepts publication-title: Int. J. Mach. Learn. Cybern. – volume: 225 start-page: 47 year: 2013 end-page: 54 ident: b6 article-title: Dual multi-adjoint concept lattices publication-title: Inform. Sci. – volume: 39 start-page: 855 year: 2009 end-page: 866 ident: b25 article-title: Interpreting concept learning in cognitive informatics and granular computing publication-title: IEEE Trans. Syst. Man Cybern. B – volume: 10 start-page: 3263 year: 2019 end-page: 3271 ident: b31 article-title: A theoretical study on object-oriented and property-oriented multi-scale formal concept analysis publication-title: Int. J. Mach. Learn. Cybern. – volume: 153 start-page: 85 year: 2003 end-page: 106 ident: b48 article-title: Maximal consistent block technique for rule acquisition in incomplete information systems publication-title: Inform. Sci. – volume: 91 start-page: 143 year: 2016 end-page: 151 ident: b4 article-title: The connections between three-way and classical concept lattices publication-title: Knowl.-Based Syst. – volume: 333 start-page: 71 year: 2018 end-page: 86 ident: b19 article-title: Constructing L-fuzzy concept lattices without fuzzy Galois closure operation publication-title: Fuzzy Sets and Systems – volume: 104 start-page: 62 year: 2016 end-page: 73 ident: b23 article-title: Granule description based on formal concept analysis publication-title: Knowl.-Based Syst. – volume: 161 year: 2023 ident: b47 article-title: Optimal scale selection and knowledge discovery in generalized multi-scale decision tables publication-title: Internat. J. Approx. Reason. – volume: 12 start-page: 1427 year: 2021 end-page: 1437 ident: b41 article-title: Entropy based optimal scale combination selection for generalized multi-scale information tables publication-title: Int. J. Mach. Learn. Cybern. – volume: 33 start-page: 3675 year: 2021 end-page: 3689 ident: b46 article-title: Optimal scale combination selection integrating three-way decision with hasse diagram publication-title: IEEE Trans. Neural Netw. Learn. Syst. – year: 2016 ident: b18 article-title: Formal Concept Analysis: Theory and Application – volume: 8 start-page: 159 year: 2017 end-page: 170 ident: b27 article-title: Cognitive concept learning from incomplete information publication-title: Int. J. Mach. Learn. Cybern. – volume: 4 start-page: 621 year: 2013 end-page: 630 ident: b30 article-title: Two kinds of multi-level formal concepts and its application for sets approximations publication-title: Int. J. Mach. Learn. Cybern. – volume: 584 start-page: 325 year: 2022 end-page: 341 ident: b51 article-title: A dynamic rule-based classification model via granular computing publication-title: Inform. Sci. – year: 2023 ident: b8 article-title: Robust variable threshold fuzzy concept lattice with application to medical diagnosis publication-title: Int. J. Fuzzy Syst. – start-page: 43 year: 1979 end-page: 53 ident: b20 article-title: Approximation in formal concept analysis publication-title: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing: 10th International Conference, Vol. 3641 – volume: 496 start-page: 65 year: 2019 end-page: 81 ident: b49 article-title: Concurrent concept-cognitive learning model for classification publication-title: Inform. Sci. – volume: 541 start-page: 36 year: 2020 end-page: 59 ident: b45 article-title: Optimal scale selection and attribute reduction in multi-scale decision tables based on three-way decision publication-title: Inform. Sci. – volume: 31 start-page: 1885 year: 2023 end-page: 1899 ident: b55 article-title: Two-way concept-cognitive learning method: A fuzzy-based progressive learning publication-title: IEEE Trans. Fuzzy Syst. – year: 2019 ident: b9 article-title: Basic Grain Computing Tutorial – volume: 346/347 start-page: 442 year: 2016 end-page: 462 ident: b24 article-title: Rough-set concept analysis: Interpreting RS-definable concepts based on ideas from formal concept analysis publication-title: Inform. Sci. – volume: 12 start-page: 281 year: 2021 end-page: 301 ident: b44 article-title: Optimal scale combination selection for multi-scale decision tables based on three-way decision publication-title: Int. J. Mach. Learn. Cybern. – volume: 103 start-page: 107 year: 2018 end-page: 123 ident: b36 article-title: Three-way decision and granular computing publication-title: Internat. J. Approx. Reason. – volume: 100 year: 2023 ident: b52 article-title: M-FCCL: Memory-based concept-cognitive learning for dynamic fuzzy data classification and knowledge fusion publication-title: Inf. Fusion – year: 1979 ident: b33 article-title: Fuzzy sets and information granularity publication-title: Advances in Fuzzy Set Theory and Applications – volume: 116 start-page: 106 year: 2020 end-page: 125 ident: b37 article-title: Three-way granular computing, rough sets, and formal concept analysis publication-title: Int. J. Approx. Reason. – year: 1999 ident: 10.1016/j.asoc.2024.111277_b1 article-title: Formal concept analysis – volume: 154 start-page: 56 year: 2023 ident: 10.1016/j.asoc.2024.111277_b12 article-title: Rule acquisition in generalized multi-scale information systems with multi-scale decisions publication-title: Internat. J. Approx. Reason. doi: 10.1016/j.ijar.2022.12.004 – start-page: 281 year: 2000 ident: 10.1016/j.asoc.2024.111277_b17 article-title: Rough set data analysis – volume: 53 start-page: 6025 issue: 5 year: 2023 ident: 10.1016/j.asoc.2024.111277_b7 article-title: Neighborhood based concept lattice publication-title: Appl. Intell. – volume: 584 start-page: 325 year: 2022 ident: 10.1016/j.asoc.2024.111277_b51 article-title: A dynamic rule-based classification model via granular computing publication-title: Inform. Sci. doi: 10.1016/j.ins.2021.10.065 – volume: 30 start-page: 3748 issue: 9 year: 2021 ident: 10.1016/j.asoc.2024.111277_b50 article-title: Fuzzy rule-based classification method for incremental rule learning publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2021.3128061 – volume: 1 start-page: 107 issue: 1 year: 1998 ident: 10.1016/j.asoc.2024.111277_b34 article-title: Granular computing on binary relations I: Data mining and neighborhood systems publication-title: Rough Sets Konwl. Discov. – volume: 541 start-page: 36 year: 2020 ident: 10.1016/j.asoc.2024.111277_b45 article-title: Optimal scale selection and attribute reduction in multi-scale decision tables based on three-way decision publication-title: Inform. Sci. doi: 10.1016/j.ins.2020.05.109 – volume: 161 year: 2023 ident: 10.1016/j.asoc.2024.111277_b47 article-title: Optimal scale selection and knowledge discovery in generalized multi-scale decision tables publication-title: Internat. J. Approx. Reason. doi: 10.1016/j.ijar.2023.108983 – volume: 91 start-page: 143 year: 2016 ident: 10.1016/j.asoc.2024.111277_b4 article-title: The connections between three-way and classical concept lattices publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2015.08.006 – volume: 339 start-page: 1 year: 2016 ident: 10.1016/j.asoc.2024.111277_b5 article-title: Lattice-theoretic contexts and their concept lattices via Galois ideals publication-title: Inform. Sci. doi: 10.1016/j.ins.2015.12.028 – volume: 298 start-page: 447 year: 2015 ident: 10.1016/j.asoc.2024.111277_b26 article-title: Concept learning via granular computing: A cognitive viewpoint publication-title: Inform. Sci. doi: 10.1016/j.ins.2014.12.010 – volume: 12 start-page: 1427 year: 2021 ident: 10.1016/j.asoc.2024.111277_b41 article-title: Entropy based optimal scale combination selection for generalized multi-scale information tables publication-title: Int. J. Mach. Learn. Cybern. doi: 10.1007/s13042-020-01243-y – volume: 225 start-page: 47 year: 2013 ident: 10.1016/j.asoc.2024.111277_b6 article-title: Dual multi-adjoint concept lattices publication-title: Inform. Sci. doi: 10.1016/j.ins.2012.10.030 – volume: 21 start-page: 1461 issue: 10 year: 2009 ident: 10.1016/j.asoc.2024.111277_b39 article-title: Granular computing and knowledge reduction in formal contexts publication-title: IEEE Trans. Knowl. Data Eng. doi: 10.1109/TKDE.2008.223 – volume: 153 start-page: 85 year: 2003 ident: 10.1016/j.asoc.2024.111277_b48 article-title: Maximal consistent block technique for rule acquisition in incomplete information systems publication-title: Inform. Sci. doi: 10.1016/S0020-0255(03)00061-6 – volume: 33 start-page: 3675 issue: 8 year: 2021 ident: 10.1016/j.asoc.2024.111277_b46 article-title: Optimal scale combination selection integrating three-way decision with hasse diagram publication-title: IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2021.3054063 – start-page: 43 year: 1979 ident: 10.1016/j.asoc.2024.111277_b20 article-title: Approximation in formal concept analysis – year: 1979 ident: 10.1016/j.asoc.2024.111277_b33 article-title: Fuzzy sets and information granularity – volume: 116 start-page: 106 year: 2020 ident: 10.1016/j.asoc.2024.111277_b37 article-title: Three-way granular computing, rough sets, and formal concept analysis publication-title: Int. J. Approx. Reason. doi: 10.1016/j.ijar.2019.11.002 – volume: 346/347 start-page: 442 year: 2016 ident: 10.1016/j.asoc.2024.111277_b24 article-title: Rough-set concept analysis: Interpreting RS-definable concepts based on ideas from formal concept analysis publication-title: Inform. Sci. doi: 10.1016/j.ins.2016.01.091 – volume: 100 year: 2023 ident: 10.1016/j.asoc.2024.111277_b52 article-title: M-FCCL: Memory-based concept-cognitive learning for dynamic fuzzy data classification and knowledge fusion publication-title: Inf. Fusion doi: 10.1016/j.inffus.2023.101962 – volume: 25 start-page: 490 issue: 5 year: 2002 ident: 10.1016/j.asoc.2024.111277_b14 article-title: Fast asymptotic construction algorithm for concept lattice publication-title: J. Comput. Sci. – year: 2019 ident: 10.1016/j.asoc.2024.111277_b9 – volume: 378 start-page: 282 year: 2017 ident: 10.1016/j.asoc.2024.111277_b13 article-title: On rule acquisition in incomplete multi-scale decision tables publication-title: Inform. Sci. doi: 10.1016/j.ins.2016.03.041 – volume: 104 start-page: 62 year: 2016 ident: 10.1016/j.asoc.2024.111277_b23 article-title: Granule description based on formal concept analysis publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2016.04.011 – volume: vol. 8818 start-page: 732 year: 2014 ident: 10.1016/j.asoc.2024.111277_b21 article-title: Three-way formal concept analysis – volume: 12 start-page: 281 year: 2021 ident: 10.1016/j.asoc.2024.111277_b44 article-title: Optimal scale combination selection for multi-scale decision tables based on three-way decision publication-title: Int. J. Mach. Learn. Cybern. doi: 10.1007/s13042-020-01173-9 – volume: 103 start-page: 107 year: 2018 ident: 10.1016/j.asoc.2024.111277_b36 article-title: Three-way decision and granular computing publication-title: Internat. J. Approx. Reason. doi: 10.1016/j.ijar.2018.09.005 – volume: 639 year: 2023 ident: 10.1016/j.asoc.2024.111277_b53 article-title: Fuzzy-based concept-cognitive learning: An investigation of novel approach to tumor diagnosis analysis publication-title: Inform. Sci. doi: 10.1016/j.ins.2023.118998 – volume: 54 start-page: 149 issue: 1 year: 2013 ident: 10.1016/j.asoc.2024.111277_b16 article-title: Incomplete decision contexts: Approximate concept construction, rule acquisition and knowledge reduction publication-title: Int. J. Approx. Reason. doi: 10.1016/j.ijar.2012.07.005 – start-page: 1349 year: 2001 ident: 10.1016/j.asoc.2024.111277_b10 article-title: Granular computing: [a]n introduction – volume: 260 start-page: 149 issue: 1 year: 2014 ident: 10.1016/j.asoc.2024.111277_b28 article-title: Granularity of attributes in formal concept analysis publication-title: Inform. Sci. doi: 10.1016/j.ins.2013.10.021 – volume: 39 start-page: 855 issue: 4 year: 2009 ident: 10.1016/j.asoc.2024.111277_b25 article-title: Interpreting concept learning in cognitive informatics and granular computing publication-title: IEEE Trans. Syst. Man Cybern. B doi: 10.1109/TSMCB.2009.2013334 – volume: 181 start-page: 3878 issue: 18 year: 2011 ident: 10.1016/j.asoc.2024.111277_b15 article-title: Theory and applications of granular labelled partitions in multi-scale decision tables publication-title: Inform. Sci. doi: 10.1016/j.ins.2011.04.047 – volume: 378 start-page: 244 year: 2017 ident: 10.1016/j.asoc.2024.111277_b22 article-title: Three-way cognitive concept learning via multi-granularity publication-title: Inform. Sci. doi: 10.1016/j.ins.2016.04.051 – year: 2016 ident: 10.1016/j.asoc.2024.111277_b18 – volume: 4 start-page: 621 year: 2013 ident: 10.1016/j.asoc.2024.111277_b30 article-title: Two kinds of multi-level formal concepts and its application for sets approximations publication-title: Int. J. Mach. Learn. Cybern. doi: 10.1007/s13042-012-0128-2 – volume: 180 start-page: 949 issue: 6 year: 2010 ident: 10.1016/j.asoc.2024.111277_b38 article-title: MGRS: A multi-granulation rough set publication-title: Inform. Sci. doi: 10.1016/j.ins.2009.11.023 – volume: 9 start-page: 1869 year: 2018 ident: 10.1016/j.asoc.2024.111277_b29 article-title: Connections between two-universe rough sets and formal concepts publication-title: Int. J. Mach. Learn. Cybern. doi: 10.1007/s13042-018-0803-z – volume: 31 start-page: 1885 issue: 6 year: 2023 ident: 10.1016/j.asoc.2024.111277_b55 article-title: Two-way concept-cognitive learning method: A fuzzy-based progressive learning publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2022.3216110 – volume: 496 start-page: 65 year: 2019 ident: 10.1016/j.asoc.2024.111277_b49 article-title: Concurrent concept-cognitive learning model for classification publication-title: Inform. Sci. doi: 10.1016/j.ins.2019.05.009 – volume: 333 start-page: 71 year: 2018 ident: 10.1016/j.asoc.2024.111277_b19 article-title: Constructing L-fuzzy concept lattices without fuzzy Galois closure operation publication-title: Fuzzy Sets and Systems doi: 10.1016/j.fss.2017.05.002 – volume: 11 start-page: 5315 year: 2020 ident: 10.1016/j.asoc.2024.111277_b32 article-title: Formal concept analysis of multi-scale formal context publication-title: J. Ambient Intell. Humaniz. Comput. doi: 10.1007/s12652-020-01867-6 – year: 2023 ident: 10.1016/j.asoc.2024.111277_b8 article-title: Robust variable threshold fuzzy concept lattice with application to medical diagnosis publication-title: Int. J. Fuzzy Syst. – volume: 115 start-page: 194 year: 2019 ident: 10.1016/j.asoc.2024.111277_b11 article-title: Generalized multi-scale decision tables with multi-scale decision attributes publication-title: Internat. J. Approx. Reason. doi: 10.1016/j.ijar.2019.09.010 – volume: 11 start-page: 961 year: 2020 ident: 10.1016/j.asoc.2024.111277_b40 article-title: A comparison study of optimal scale combination selection in generalized multi-scale decision tables publication-title: Int. J. Mach. Learn. Cybern. doi: 10.1007/s13042-019-00954-1 – year: 2023 ident: 10.1016/j.asoc.2024.111277_b54 article-title: Fuzzy-granular concept-cognitive learning via three-way decision: Performance evaluation on dynamic knowledge discovery publication-title: IEEE Trans. Fuzzy Syst. – volume: 8 start-page: 159 year: 2017 ident: 10.1016/j.asoc.2024.111277_b27 article-title: Cognitive concept learning from incomplete information publication-title: Int. J. Mach. Learn. Cybern. doi: 10.1007/s13042-016-0553-8 – volume: 264 start-page: 196 year: 2014 ident: 10.1016/j.asoc.2024.111277_b42 article-title: Pessimistic rough set based decisions: A multi-granulation fusion strategy publication-title: Inform. Sci. doi: 10.1016/j.ins.2013.12.014 – volume: 10 start-page: 2327 year: 2019 ident: 10.1016/j.asoc.2024.111277_b3 article-title: Concept lattice simplification in formal concept analysis using attribute clustering publication-title: J. Ambient Intell. Humaniz. Comput. doi: 10.1007/s12652-018-0831-2 – volume: 16 start-page: 87 issue: 1 year: 2001 ident: 10.1016/j.asoc.2024.111277_b35 article-title: Information granulation and rough set approximation publication-title: Int. J. Intell. Syst. doi: 10.1002/1098-111X(200101)16:1<87::AID-INT7>3.0.CO;2-S – volume: 11 start-page: 1095 year: 2020 ident: 10.1016/j.asoc.2024.111277_b43 article-title: Optimal scale selection by integrating uncertainty and cost-sensitive learning in multi-scale decision tables publication-title: Int. J. Mach. Learn. Cybern. doi: 10.1007/s13042-020-01101-x – volume: 10 start-page: 3263 year: 2019 ident: 10.1016/j.asoc.2024.111277_b31 article-title: A theoretical study on object-oriented and property-oriented multi-scale formal concept analysis publication-title: Int. J. Mach. Learn. Cybern. doi: 10.1007/s13042-019-01015-3 – volume: 10 start-page: 823 issue: 6 year: 2000 ident: 10.1016/j.asoc.2024.111277_b2 article-title: Similarity relations in concept lattices publication-title: J. Logic Comput. doi: 10.1093/logcom/10.6.823 |
| SSID | ssj0016928 |
| Score | 2.4283736 |
| Snippet | The classification of multi-scale data is an important research topic in granular computing. Its research goal is to determine the most appropriate scale and... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 111277 |
| SubjectTerms | Classification Generalized multi-scale formal context Multi-objective optimization methods Optimal scale selection criteria |
| Title | Optimal scale selection approach for classification based on generalized multi-scale formal context |
| URI | https://dx.doi.org/10.1016/j.asoc.2024.111277 |
| Volume | 152 |
| WOSCitedRecordID | wos001166171700001&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: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 issn: 1568-4946 databaseCode: AIEXJ dateStart: 20010601 customDbUrl: isFulltext: true dateEnd: 99991231 titleUrlDefault: https://www.sciencedirect.com omitProxy: false ssIdentifier: ssj0016928 providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3JTsMwELXKcuDCjtjlAzeUKm2cxUeEQIAQcOihnIIzTqCopIi2CPH1jLc0rIIDFyu1kknUeXoe288zhOxB4kc4Pc48yJLAY1nEPS5w4iplLDIIolhmOs_seXxxkXS7_KrRuHFnYZ77cVkmLy_88V9djX3obHV09g_uroxiB16j07FFt2P7K8dfIgk86KOOyP37Q13nRmuObfZwLSwEFTQrlZDxvxrLpNo3uDVZqHuv-FNrDT1jRoe2fS1sRzavR7QujB0in2uB-njkRkO9Tm-45DjvVdIfrR8465V3ouq7Hput_0F5C6qpr0W0mZMvT-gzSjzG7aKi41eTotYyJHJr2xRu-UTeZh3hvikQl01lvjm5-X2m7A8jWKUrdJK1-1TZSJWN1NiYIjPtOORI3TMHp0fds2qnKeK6_m715fZgldEAfvySr4OXWkDSWSTzdiZBDwwClkgjL5fJgqvSQS1prxCwgKDak7QCBHWAoOhc-h4QVAOC4kUNELQGCGoAQS0gVknn-KhzeOLZ0hoeBL4_8iLgOWOiJUOZsSJMCoAiSSAosgxjfFW8SLBCqNoGXEKOU3IGUsQAfiFEW7JgjUyXgzJfJ1Rif8wiERY-YypdYA44cEEYSdkSMuYbpOX-shRs2nlV_aSffu-sDbJfPfNokq78eHfoPJHasNGEgykC64fnNv_0li0yN0H8NpkePY3zHTILz6Pe8GnXouoN-sSSBw |
| linkProvider | Elsevier |
| 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=Optimal+scale+selection+approach+for+classification+based+on+generalized+multi-scale+formal+context&rft.jtitle=Applied+soft+computing&rft.au=Wang%2C+Fei&rft.au=Li%2C+Jinhai&rft.au=Yu%2C+Chongchong&rft.date=2024-02-01&rft.issn=1568-4946&rft.volume=152&rft.spage=111277&rft_id=info:doi/10.1016%2Fj.asoc.2024.111277&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_asoc_2024_111277 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1568-4946&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1568-4946&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1568-4946&client=summon |