No Cover Image

Conference Paper/Proceeding/Abstract 1451 views

Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths

F. Zaidi, D. Archambault, G. Melançon, Daniel Archambault Orcid Logo

Advances in Data Mining. Applications and Theoretical Aspects, Volume: 6171 LNAI, Pages: 42 - 56

Swansea University Author: Daniel Archambault Orcid Logo

Full text not available from this repository: check for access using links below.

DOI (Published version): 10.1007/978-3-642-14400-4_4

Published in: Advances in Data Mining. Applications and Theoretical Aspects
ISBN: 978-3-642-14399-1 978-3-642-14400-4
Published: 2010
Online Access: http://www.scopus.com/inward/record.url?eid=2-s2.0-77954867692&partnerID=MN8TOARS
URI: https://cronfa.swan.ac.uk/Record/cronfa23049
first_indexed 2015-09-12T02:08:27Z
last_indexed 2018-02-09T05:01:46Z
id cronfa23049
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2015-09-11T09:18:02.4061490</datestamp><bib-version>v2</bib-version><id>23049</id><entry>2015-09-11</entry><title>Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths</title><swanseaauthors><author><sid>8fa6987716a22304ef04d3c3d50ef266</sid><ORCID>0000-0003-4978-8479</ORCID><firstname>Daniel</firstname><surname>Archambault</surname><name>Daniel Archambault</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2015-09-11</date><deptcode>MACS</deptcode><abstract></abstract><type>Conference Paper/Proceeding/Abstract</type><journal>Advances in Data Mining. Applications and Theoretical Aspects</journal><volume>6171 LNAI</volume><paginationStart>42</paginationStart><paginationEnd>56</paginationEnd><publisher/><isbnPrint>978-3-642-14399-1</isbnPrint><isbnElectronic>978-3-642-14400-4</isbnElectronic><keywords/><publishedDay>31</publishedDay><publishedMonth>12</publishedMonth><publishedYear>2010</publishedYear><publishedDate>2010-12-31</publishedDate><doi>10.1007/978-3-642-14400-4_4</doi><url>http://www.scopus.com/inward/record.url?eid=2-s2.0-77954867692&amp;amp;partnerID=MN8TOARS</url><notes>@article archambault2010,title = Evaluating the quality of clustering algorithms using cluster path lengths,journal = Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),year = 2010,volume = 6171 LNAI,pages = 42-56,author = Zaidi, F. and Archambault, D. and Melan&#xE7;on, G.</notes><college>COLLEGE NANME</college><department>Mathematics and Computer Science School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MACS</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2015-09-11T09:18:02.4061490</lastEdited><Created>2015-09-11T09:14:17.8115093</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Mathematics and Computer Science - Computer Science</level></path><authors><author><firstname>F.</firstname><surname>Zaidi</surname><order>1</order></author><author><firstname>D.</firstname><surname>Archambault</surname><order>2</order></author><author><firstname>G.</firstname><surname>Melan&#xE7;on</surname><order>3</order></author><author><firstname>Daniel</firstname><surname>Archambault</surname><orcid>0000-0003-4978-8479</orcid><order>4</order></author></authors><documents/><OutputDurs/></rfc1807>
spelling 2015-09-11T09:18:02.4061490 v2 23049 2015-09-11 Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths 8fa6987716a22304ef04d3c3d50ef266 0000-0003-4978-8479 Daniel Archambault Daniel Archambault true false 2015-09-11 MACS Conference Paper/Proceeding/Abstract Advances in Data Mining. Applications and Theoretical Aspects 6171 LNAI 42 56 978-3-642-14399-1 978-3-642-14400-4 31 12 2010 2010-12-31 10.1007/978-3-642-14400-4_4 http://www.scopus.com/inward/record.url?eid=2-s2.0-77954867692&amp;partnerID=MN8TOARS @article archambault2010,title = Evaluating the quality of clustering algorithms using cluster path lengths,journal = Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),year = 2010,volume = 6171 LNAI,pages = 42-56,author = Zaidi, F. and Archambault, D. and Melançon, G. COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University 2015-09-11T09:18:02.4061490 2015-09-11T09:14:17.8115093 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science F. Zaidi 1 D. Archambault 2 G. Melançon 3 Daniel Archambault 0000-0003-4978-8479 4
title Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths
spellingShingle Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths
Daniel Archambault
title_short Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths
title_full Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths
title_fullStr Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths
title_full_unstemmed Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths
title_sort Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths
author_id_str_mv 8fa6987716a22304ef04d3c3d50ef266
author_id_fullname_str_mv 8fa6987716a22304ef04d3c3d50ef266_***_Daniel Archambault
author Daniel Archambault
author2 F. Zaidi
D. Archambault
G. Melançon
Daniel Archambault
format Conference Paper/Proceeding/Abstract
container_title Advances in Data Mining. Applications and Theoretical Aspects
container_volume 6171 LNAI
container_start_page 42
publishDate 2010
institution Swansea University
isbn 978-3-642-14399-1
978-3-642-14400-4
doi_str_mv 10.1007/978-3-642-14400-4_4
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
url http://www.scopus.com/inward/record.url?eid=2-s2.0-77954867692&amp;partnerID=MN8TOARS
document_store_str 0
active_str 0
published_date 2010-12-31T18:15:31Z
_version_ 1850693157578080256
score 11.088971

Similar Items