MultiClusterTree: Interactive Visual Exploration of Hierarchical Clusters in Multidimensional Multivariate Data
Visual analytics of multidimensional multivariate data is a challenging task because of the difficulty in understanding metrics in attribute spaces with more than three dimensions. Frequently, the analysis goal is not to look into individual records but to understand the distribution of the records...
Saved in:
| Published in: | Computer graphics forum Vol. 28; no. 3; pp. 823 - 830 |
|---|---|
| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Oxford, UK
Blackwell Publishing Ltd
01.06.2009
|
| Subjects: | |
| ISSN: | 0167-7055, 1467-8659 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | Visual analytics of multidimensional multivariate data is a challenging task because of the difficulty in understanding metrics in attribute spaces with more than three dimensions. Frequently, the analysis goal is not to look into individual records but to understand the distribution of the records at large and to find clusters of records with similar attribute values. A large number of (typically hierarchical) clustering algorithms have been developed to group individual records to clusters of statistical significance. However, only few visualization techniques exist for further exploring and understanding the clustering results. We propose visualization and interaction methods for analyzing individual clusters as well as cluster distribution within and across levels in the cluster hierarchy. We also provide a clustering method that operates on density rather than individual records. To not restrict our search for clusters, we compute density in the given multidimensional multivariate space. Clusters are formed by areas of high density. We present an approach that automatically computes a hierarchical tree of high density clusters. To visually represent the cluster hierarchy, we present a 2D radial layout that supports an intuitive understanding of the distribution structure of the multidimensional multivariate data set. Individual clusters can be explored interactively using parallel coordinates when being selected in the cluster tree. Furthermore, we integrate circular parallel coordinates into the radial hierarchical cluster tree layout, which allows for the analysis of the overall cluster distribution. This visual representation supports the comprehension of the relations between clusters and the original attributes. The combination of the 2D radial layout and the circular parallel coordinates is used to overcome the overplotting problem of parallel coordinates when looking into data sets with many records. We apply an automatic coloring scheme based on the 2D radial layout of the hierarchical cluster tree encoding hue, saturation, and value of the HSV color space. The colors support linking the 2D radial layout to other views such as the standard parallel coordinates or, in case data is obtained from multidimensional spatial data, the distribution in object space. |
|---|---|
| AbstractList | Visual analytics of multidimensional multivariate data is a challenging task because of the difficulty in understanding metrics in attribute spaces with more than three dimensions. Frequently, the analysis goal is not to look into individual records but to understand the distribution of the records at large and to find clusters of records with similar attribute values. A large number of (typically hierarchical) clustering algorithms have been developed to group individual records to clusters of statistical significance. However, only few visualization techniques exist for further exploring and understanding the clustering results. We propose visualization and interaction methods for analyzing individual clusters as well as cluster distribution within and across levels in the cluster hierarchy. We also provide a clustering method that operates on density rather than individual records. To not restrict our search for clusters, we compute density in the given multidimensional multivariate space. Clusters are formed by areas of high density. We present an approach that automatically computes a hierarchical tree of high density clusters. To visually represent the cluster hierarchy, we present a 2D radial layout that supports an intuitive understanding of the distribution structure of the multidimensional multivariate data set. Individual clusters can be explored interactively using parallel coordinates when being selected in the cluster tree. Furthermore, we integrate circular parallel coordinates into the radial hierarchical cluster tree layout, which allows for the analysis of the overall cluster distribution. This visual representation supports the comprehension of the relations between clusters and the original attributes. The combination of the 2D radial layout and the circular parallel coordinates is used to overcome the overplotting problem of parallel coordinates when looking into data sets with many records. We apply an automatic coloring scheme based on the 2D radial layout of the hierarchical cluster tree encoding hue, saturation, and value of the HSV color space. The colors support linking the 2D radial layout to other views such as the standard parallel coordinates or, in case data is obtained from multidimensional spatial data, the distribution in object space. [PUBLICATION ABSTRACT] Visual analytics of multidimensional multivariate data is a challenging task because of the difficulty in understanding metrics in attribute spaces with more than three dimensions. Frequently, the analysis goal is not to look into individual records but to understand the distribution of the records at large and to find clusters of records with similar attribute values. A large number of (typically hierarchical) clustering algorithms have been developed to group individual records to clusters of statistical significance. However, only few visualization techniques exist for further exploring and understanding the clustering results. We propose visualization and interaction methods for analyzing individual clusters as well as cluster distribution within and across levels in the cluster hierarchy. We also provide a clustering method that operates on density rather than individual records. To not restrict our search for clusters, we compute density in the given multidimensional multivariate space. Clusters are formed by areas of high density. We present an approach that automatically computes a hierarchical tree of high density clusters. To visually represent the cluster hierarchy, we present a 2D radial layout that supports an intuitive understanding of the distribution structure of the multidimensional multivariate data set. Individual clusters can be explored interactively using parallel coordinates when being selected in the cluster tree. Furthermore, we integrate circular parallel coordinates into the radial hierarchical cluster tree layout, which allows for the analysis of the overall cluster distribution. This visual representation supports the comprehension of the relations between clusters and the original attributes. The combination of the 2D radial layout and the circular parallel coordinates is used to overcome the overplotting problem of parallel coordinates when looking into data sets with many records. We apply an automatic coloring scheme based on the 2D radial layout of the hierarchical cluster tree encoding hue, saturation, and value of the HSV color space. The colors support linking the 2D radial layout to other views such as the standard parallel coordinates or, in case data is obtained from multidimensional spatial data, the distribution in object space. |
| Author | Linsen, Lars Van Long, Tran |
| Author_xml | – sequence: 1 givenname: Tran surname: Van Long fullname: Van Long, Tran organization: School of Engineering and Science Jacobs University Bremen, Germany – sequence: 2 givenname: Lars surname: Linsen fullname: Linsen, Lars organization: School of Engineering and Science Jacobs University Bremen, Germany |
| BookMark | eNqNUctuGyEURVUq1Un6D6iL7mbKMDCPSq1UuYmdKG037kPdoDv4joqLBweY1Pn7MnaURVZhw4XzEJxzSk4GNyAhtGB5kda7TV6Iqs6aSrY5Z6zNWTo3-f4FmT0CJ2TGijTXTMpX5DSEDWNM1JWcEfdltNHM7Rgi-pVHfE-vhjSCjuYO6Q8TRrD0Yr-zzkM0bqCup0uTCF7_MTphD9pAzUAPZmuzxSEkagIPF3fgDUSknyHCOXnZgw34-mE_I98vL1bzZXbzbXE1_3STacHaJgPNsBAcawDZoUQUPeeyRQ0FCC7LVjOBfN2h6DrRtVC1fF3260RHEIzp8oy8PfruvLsdMUS1NUGjtTCgG4Mq0_dTJDwR3zwhbtzo09uDKlpRyUqULJE-HknauxA89kqbeIgjejBWFUxNZaiNmjJXU-ZqKkMdylD7ZNA8Mdh5swV__xzph6P0n7F4_2ydmi8upynps6PepJr2j3rwf1VVl7VUP78uFL_-tWqWv4Valf8B1wK19g |
| CitedBy_id | crossref_primary_10_1007_s12650_019_00584_3 crossref_primary_10_1145_3340960 crossref_primary_10_1080_13658816_2010_513982 crossref_primary_10_1109_TVCG_2021_3061925 crossref_primary_10_1111_cgf_14034 crossref_primary_10_1186_1471_2105_15_S6_S4 crossref_primary_10_3390_informatics4030021 crossref_primary_10_1016_j_bdr_2019_07_001 crossref_primary_10_1109_TVCG_2013_150 crossref_primary_10_1109_TVCG_2010_138 crossref_primary_10_1002_widm_1093 crossref_primary_10_1177_1473871613481692 crossref_primary_10_1109_TVCG_2021_3057519 |
| Cites_doi | 10.1109/MC.2002.1016905 10.1007/BF01898350 10.1145/304182.304187 10.1111/j.1467-8659.2008.01239.x 10.1080/01621459.1990.10474926 10.1007/BF01908064 10.2307/3315985 10.1057/palgrave.ivs.9500117 |
| ContentType | Journal Article |
| Copyright | 2009 The Author(s) Journal compilation © 2009 The Eurographics Association and Blackwell Publishing Ltd. 2009 The Eurographics Association and Blackwell Publishing Ltd. |
| Copyright_xml | – notice: 2009 The Author(s) Journal compilation © 2009 The Eurographics Association and Blackwell Publishing Ltd. – notice: 2009 The Eurographics Association and Blackwell Publishing Ltd. |
| DBID | BSCLL AAYXX CITATION 7SC 8FD JQ2 L7M L~C L~D F28 FR3 |
| DOI | 10.1111/j.1467-8659.2009.01468.x |
| DatabaseName | Istex CrossRef Computer and Information Systems Abstracts Technology Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional ANTE: Abstracts in New Technology & Engineering Engineering Research Database |
| DatabaseTitle | CrossRef Computer and Information Systems Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic Advanced Technologies Database with Aerospace ProQuest Computer Science Collection Computer and Information Systems Abstracts Professional Engineering Research Database ANTE: Abstracts in New Technology & Engineering |
| DatabaseTitleList | Computer and Information Systems Abstracts Technology Research Database CrossRef |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 1467-8659 |
| EndPage | 830 |
| ExternalDocumentID | 1810708741 10_1111_j_1467_8659_2009_01468_x CGF1468 ark_67375_WNG_2JXT8HZ4_T |
| Genre | article Feature |
| GroupedDBID | .3N .4S .DC .GA .Y3 05W 0R~ 10A 15B 1OB 1OC 29F 31~ 33P 3SF 4.4 50Y 50Z 51W 51X 52M 52N 52O 52P 52S 52T 52U 52W 52X 5GY 5HH 5LA 5VS 66C 6J9 702 7PT 8-0 8-1 8-3 8-4 8-5 8UM 8VB 930 A03 AAESR AAEVG AAHQN AAMMB AAMNL AANHP AANLZ AAONW AASGY AAXRX AAYCA AAZKR ABCQN ABCUV ABDBF ABDPE ABEML ABPVW ACAHQ ACBWZ ACCZN ACFBH ACGFS ACPOU ACRPL ACSCC ACUHS ACXBN ACXQS ACYXJ ADBBV ADEOM ADIZJ ADKYN ADMGS ADMLS ADNMO ADOZA ADXAS ADZMN AEFGJ AEGXH AEIGN AEIMD AEMOZ AENEX AEUYR AEYWJ AFBPY AFEBI AFFNX AFFPM AFGKR AFWVQ AFZJQ AGHNM AGQPQ AGXDD AGYGG AHBTC AHEFC AHQJS AIDQK AIDYY AIQQE AITYG AIURR AJXKR AKVCP ALAGY ALMA_UNASSIGNED_HOLDINGS ALUQN ALVPJ AMBMR AMYDB ARCSS ASPBG ATUGU AUFTA AVWKF AZBYB AZFZN AZVAB BAFTC BDRZF BFHJK BHBCM BMNLL BMXJE BNHUX BROTX BRXPI BSCLL BY8 CAG COF CS3 CWDTD D-E D-F DCZOG DPXWK DR2 DRFUL DRSTM DU5 EAD EAP EBA EBO EBR EBS EBU EDO EJD EMK EST ESX F00 F01 F04 F5P FEDTE FZ0 G-S G.N GODZA H.T H.X HF~ HGLYW HVGLF HZI HZ~ I-F IHE IX1 J0M K1G K48 LATKE LC2 LC3 LEEKS LH4 LITHE LOXES LP6 LP7 LUTES LW6 LYRES MEWTI MK4 MRFUL MRSTM MSFUL MSSTM MXFUL MXSTM N04 N05 N9A NF~ O66 O9- OIG P2W P2X P4D PALCI PQQKQ Q.N Q11 QB0 QWB R.K RDJ RIWAO RJQFR ROL RX1 SAMSI SUPJJ TH9 TN5 TUS UB1 V8K W8V W99 WBKPD WIH WIK WOHZO WQJ WXSBR WYISQ WZISG XG1 ZL0 ZZTAW ~IA ~IF ~WT AAYXX CITATION O8X 7SC 8FD JQ2 L7M L~C L~D F28 FR3 |
| ID | FETCH-LOGICAL-c4098-ac0e142e7aa5be5ee4f2259eca1a42539c04e2dbe4bb4b9a692d3fd7aaea400c3 |
| IEDL.DBID | DRFUL |
| ISICitedReferencesCount | 19 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000268217500016&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0167-7055 |
| IngestDate | Tue Aug 05 09:02:34 EDT 2025 Fri Jul 25 23:43:31 EDT 2025 Sat Nov 29 03:41:04 EST 2025 Tue Nov 18 22:01:33 EST 2025 Sun Sep 21 06:19:33 EDT 2025 Sun Sep 21 06:22:00 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 3 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c4098-ac0e142e7aa5be5ee4f2259eca1a42539c04e2dbe4bb4b9a692d3fd7aaea400c3 |
| Notes | ArticleID:CGF1468 istex:3F3BB216D4BC9A8ACC62B176C05A35F70B8802A2 ark:/67375/WNG-2JXT8HZ4-T SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-2 content type line 23 |
| PQID | 194656430 |
| PQPubID | 30877 |
| PageCount | 8 |
| ParticipantIDs | proquest_miscellaneous_34761672 proquest_journals_194656430 crossref_citationtrail_10_1111_j_1467_8659_2009_01468_x crossref_primary_10_1111_j_1467_8659_2009_01468_x wiley_primary_10_1111_j_1467_8659_2009_01468_x_CGF1468 istex_primary_ark_67375_WNG_2JXT8HZ4_T |
| PublicationCentury | 2000 |
| PublicationDate | June 2009 |
| PublicationDateYYYYMMDD | 2009-06-01 |
| PublicationDate_xml | – month: 06 year: 2009 text: June 2009 |
| PublicationDecade | 2000 |
| PublicationPlace | Oxford, UK |
| PublicationPlace_xml | – name: Oxford, UK – name: Oxford |
| PublicationTitle | Computer graphics forum |
| PublicationYear | 2009 |
| Publisher | Blackwell Publishing Ltd |
| Publisher_xml | – name: Blackwell Publishing Ltd |
| References | Jain A. K. (e_1_2_6_2_17_2) 1988 Scott D. W. (e_1_2_6_2_24_2) 2004 e_1_2_6_2_19_2 e_1_2_6_2_18_2 e_1_2_6_2_16_2 e_1_2_6_2_20_2 e_1_2_6_2_21_2 e_1_2_6_2_14_2 e_1_2_6_2_22_2 e_1_2_6_2_23_2 Fayyad U. (e_1_2_6_2_11_2) 2002 Card S. K. (e_1_2_6_2_9_2) 1999 Tollis I. G. (e_1_2_6_2_25_2) 1999 Duda R. O. (e_1_2_6_2_10_2) 2001 Wegman E. J. (e_1_2_6_2_27_2) 1990; 21 e_1_2_6_2_12_2 Han J. (e_1_2_6_2_15_2) 2006 e_1_2_6_2_26_2 Wong A. (e_1_2_6_2_28_2) 1983; 45 e_1_2_6_2_7_2 e_1_2_6_2_6_2 e_1_2_6_2_29_2 e_1_2_6_2_5_2 Cormen T. H. (e_1_2_6_2_8_2) 2001 Hartigan J. A. (e_1_2_6_2_13_2) 1975 |
| References_xml | – ident: e_1_2_6_2_23_2 doi: 10.1109/MC.2002.1016905 – volume-title: Data Mining: Concepts and Techniques year: 2006 ident: e_1_2_6_2_15_2 – volume-title: Clustering Algorithms year: 1975 ident: e_1_2_6_2_13_2 – ident: e_1_2_6_2_22_2 – ident: e_1_2_6_2_20_2 – volume-title: Graph Drawing: Algorithms for the Visualization of Graphs year: 1999 ident: e_1_2_6_2_25_2 – ident: e_1_2_6_2_26_2 – ident: e_1_2_6_2_16_2 doi: 10.1007/BF01898350 – ident: e_1_2_6_2_29_2 – volume-title: Information Visualization in Data Mining and Knowledge Discovery year: 2002 ident: e_1_2_6_2_11_2 – ident: e_1_2_6_2_18_2 – ident: e_1_2_6_2_5_2 doi: 10.1145/304182.304187 – ident: e_1_2_6_2_21_2 doi: 10.1111/j.1467-8659.2008.01239.x – volume-title: Pattern Classification year: 2001 ident: e_1_2_6_2_10_2 – volume: 21 start-page: 664 year: 1990 ident: e_1_2_6_2_27_2 article-title: Hyper‐dimensional data analysis using parallel coordinates publication-title: Journal of the American Statistical Association doi: 10.1080/01621459.1990.10474926 – ident: e_1_2_6_2_14_2 doi: 10.1007/BF01908064 – ident: e_1_2_6_2_6_2 – volume-title: Readings in Information Visualization: Using Vision to Think year: 1999 ident: e_1_2_6_2_9_2 – ident: e_1_2_6_2_12_2 – ident: e_1_2_6_2_7_2 doi: 10.2307/3315985 – volume-title: Introduction to Algorithms, Second Edition year: 2001 ident: e_1_2_6_2_8_2 – volume-title: Algorithms for Clustering Data year: 1988 ident: e_1_2_6_2_17_2 – volume: 45 start-page: 362 year: 1983 ident: e_1_2_6_2_28_2 article-title: A kth nearest neighbor clustering procedure publication-title: Journal of the Royal Statistical Society, Series B – ident: e_1_2_6_2_19_2 doi: 10.1057/palgrave.ivs.9500117 – volume-title: Multidimensional Density Estimation, in Handbook of Statistics, Vol 23: Data Mining and Computational Statistics, Edited by C.R. Rao and E.J. Wegman year: 2004 ident: e_1_2_6_2_24_2 |
| SSID | ssj0004765 |
| Score | 2.0302777 |
| Snippet | Visual analytics of multidimensional multivariate data is a challenging task because of the difficulty in understanding metrics in attribute spaces with more... |
| SourceID | proquest crossref wiley istex |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 823 |
| SubjectTerms | Algorithms Clustering Computer graphics Computer Graphics [I.3.3]: Picture/Image Generation-Display Algorithms Datasets Multivariate analysis Spatial data Statistical significance Studies Visualization |
| Title | MultiClusterTree: Interactive Visual Exploration of Hierarchical Clusters in Multidimensional Multivariate Data |
| URI | https://api.istex.fr/ark:/67375/WNG-2JXT8HZ4-T/fulltext.pdf https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fj.1467-8659.2009.01468.x https://www.proquest.com/docview/194656430 https://www.proquest.com/docview/34761672 |
| Volume | 28 |
| WOSCitedRecordID | wos000268217500016&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: PRVWIB databaseName: Wiley Online Library Full Collection 2020 customDbUrl: eissn: 1467-8659 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0004765 issn: 0167-7055 databaseCode: DRFUL dateStart: 19970101 isFulltext: true titleUrlDefault: https://onlinelibrary.wiley.com providerName: Wiley-Blackwell |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Lb9swDCaGZIftsPcwr3voMOzmwQ_Jlnob0qXBUATDkHbBLoIk00DQwBnipOjPryg7WYPtUAy7WqZgUyRFUeRHgA9-j0Ws6zyWeW2phZmIlZAmls4JhdbKPEApXZyV06mcz9W3Pv-JamE6fIh9wI00I9hrUnBj2z-VXBZC9bCTVEX0yfuTw8yLMR_A8OT7-Pzsd5VkWYgd0jdhyBzm9fx1roPNakh8vz7wRG_7s2FDGj_-n7_yBB71bin73MnRU7iHzTN4eAus8DmsQq3uaLklaIXZGvGYhXCiCRaTXSzarZ-hy-kLy81WNZssqMA59FtZsp62ZYuGhckqai3QwYJ0D678yd07v-zEbMwLOB9_mY0mcd-uIXacUEmNSzDlGZbGCIsCkdfeWCh0JjXeMuTKJRyzyiK3lltlCpVVeV3519F4S-LylzBoVg2-AlYghSeFs6lCnrnKKisTp1xZG5UUCiMod-uiXY9lTi01lvrgTFNqYil12lQ6sFRfR5DuKX91eB53oPkYln5PYNaXlA9XCv1jeqqzr_OZnPzkehbB0U42dG8KWp0qgqTjeRLB-_2o12G6mDENrratzr1oeqnMIiiCmNz5y_TolOAS5Ot_JTyCB931GIWV3sBgs97iW7jvrjaLdv2u16AbleEbYQ |
| linkProvider | Wiley-Blackwell |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Lj9MwEB6hFgk48EaEBdYHxC0oDzuJuaEu3QKlQii7VFws25lIFVWKmna1Px-Pk5at4LBCXOOMldgz4_HY830Ar9wai1jXaViktSEKMxFKUeiwsFZINKZIPZTS-TSfzYr5XH7p6YCoFqbDh9gn3MgyvL8mA6eE9J9WXmRC9riTVEb0xgWUQ-60SgxgePJ1fDb9XSaZZ2IH9U0gMocXe_7a18FqNaSBvzwIRa8GtH5FGt_7r_9yH-72gSl712nSA7iBzUO4cwWu8BGsfLXuaLklcIVyjfiW-YSi9j6TnS_areuhu9XnJ5ytajZZUImzZ1xZsl62ZYuG-c4qIhfogEG6Bxdu7-7CX3aiN_oxnI3fl6NJ2BM2hJYTLqm2EcY8wVxrYVAg8tq5C4lWx9r5hlTaiGNSGeTGcCN1JpMqrSv3OmrnS2z6BAbNqsGnwDKkBKWwJpbIE1sZaYrISpvXWkaZxADy3cQo26OZE6nGUh3sanJFQ0pcm1L5IVWXAcR7yZ8dosc1ZF77ud8L6PUPuhGXC_VtdqqSj_OymHznqgzgaKccqncGrYolgdLxNArgeN_qrJiOZnSDq22rUqebTi2TADKvJ9f-MjU6JcCE4tm_Ch7DrUn5eaqmH2afjuB2d1hGSabnMNist_gCbtqLzaJdv-zN6ReR3R9R |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3db9MwED-hFSF4GJ8TYcD8gHgLyoedxLyhlq5AVU2oGxUvlu1cpIoqnZp22p8_n5OWVfAwIV7jnJXYd-fz2ff7AbxzayxiVaVhkVaGKMxEKEWhw8JaIdGYIvVQShfjfDIpZjN51tEBUS1Miw-xS7iRZXh_TQaOl2X1p5UXmZAd7iSVEX1wAWWPC5k5K-0Nvg_Px7_LJPNMbKG-CURm_2LPX_vaW616NPDXe6Ho7YDWr0jDx__1X57AYReYsk-tJj2Fe1g_g0e34Aqfw9JX6_YXGwJXmK4QPzKfUNTeZ7KLebNxPbS3-vyEs2XFRnMqcfaMKwvWyTZsXjPfWUnkAi0wSPvgyu3dXfjLBnqtX8D58PO0Pwo7wobQcsIl1TbCmCeYay0MCkReOXch0epYO9-QShtxTEqD3BhupM5kUqZV6V5H7XyJTY_goF7W-BJYhpSgFNbEEnliSyNNEVlp80rLKJMYQL6dGGU7NHMi1ViovV1NrmhIiWtTKj-k6jqAeCd52SJ63EHmvZ_7nYBe_aIbcblQPyanKvk6mxajn1xNAzjeKofqnEGjYkmgdDyNAjjZtTorpqMZXeNy06jU6aZTyySAzOvJnb9M9U8JMKF49a-CJ_DgbDBU4y-Tb8fwsD0roxzTazhYrzb4Bu7bq_W8Wb3trOkG7VQezA |
| 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=MultiClusterTree%3A+Interactive+Visual+Exploration+of+Hierarchical+Clusters+in+Multidimensional+Multivariate+Data&rft.jtitle=Computer+graphics+forum&rft.au=Van+Long%2C+Tran&rft.au=Linsen%2C+Lars&rft.date=2009-06-01&rft.pub=Blackwell+Publishing+Ltd&rft.issn=0167-7055&rft.eissn=1467-8659&rft.volume=28&rft.issue=3&rft.spage=823&rft.epage=830&rft_id=info:doi/10.1111%2Fj.1467-8659.2009.01468.x&rft.externalDBID=10.1111%252Fj.1467-8659.2009.01468.x&rft.externalDocID=CGF1468 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0167-7055&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0167-7055&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0167-7055&client=summon |