{"id":"https://openalex.org/W2744451740","doi":"https://doi.org/10.23919/icif.2017.8009784","title":"A new multi-layer clustering ensemble framework based on different closeness measures","display_name":"A new multi-layer clustering ensemble framework based on different closeness measures","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2744451740","doi":"https://doi.org/10.23919/icif.2017.8009784","mag":"2744451740"},"language":"en","primary_location":{"id":"doi:10.23919/icif.2017.8009784","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2017.8009784","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 20th International Conference on Information Fusion (Fusion)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060364502","display_name":"Shaoyi Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shaoyi Liang","raw_affiliation_strings":["Institute of Integrated Automation, Xi'an Jiaotong University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Institute of Integrated Automation, Xi'an Jiaotong University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024649502","display_name":"Deqiang Han","orcid":"https://orcid.org/0000-0001-5603-796X"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deqiang Han","raw_affiliation_strings":["Institute of Integrated Automation, Xi'an Jiaotong University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Institute of Integrated Automation, Xi'an Jiaotong University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5060364502"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10140705,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7553073763847351},{"id":"https://openalex.org/keywords/closeness","display_name":"Closeness","score":0.7222625017166138},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.67018723487854},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.5809722542762756},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32212769985198975},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24375054240226746},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.15349364280700684},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09339496493339539},{"id":"https://openalex.org/keywords/nanotechnology","display_name":"Nanotechnology","score":0.04464244842529297}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7553073763847351},{"id":"https://openalex.org/C2779545769","wikidata":"https://www.wikidata.org/wiki/Q5135364","display_name":"Closeness","level":2,"score":0.7222625017166138},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.67018723487854},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5809722542762756},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32212769985198975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24375054240226746},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.15349364280700684},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09339496493339539},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.04464244842529297},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/icif.2017.8009784","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2017.8009784","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 20th International Conference on Information Fusion (Fusion)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W100104462","https://openalex.org/W1547480755","https://openalex.org/W1570587793","https://openalex.org/W1919721856","https://openalex.org/W1967761844","https://openalex.org/W1978348710","https://openalex.org/W1981573888","https://openalex.org/W1983293338","https://openalex.org/W1987839426","https://openalex.org/W2027773397","https://openalex.org/W2096285766","https://openalex.org/W2097637261","https://openalex.org/W2116520778","https://openalex.org/W2116984363","https://openalex.org/W2130851950","https://openalex.org/W2137002202","https://openalex.org/W2139280638","https://openalex.org/W2141585940","https://openalex.org/W2145165282","https://openalex.org/W2158854411","https://openalex.org/W2735248384","https://openalex.org/W2911754149","https://openalex.org/W4285719527","https://openalex.org/W6646284504","https://openalex.org/W6674645192","https://openalex.org/W6677307600","https://openalex.org/W6681324376"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2156910174","https://openalex.org/W1995054232","https://openalex.org/W2011510925","https://openalex.org/W1557920161","https://openalex.org/W1556709767","https://openalex.org/W1993023208","https://openalex.org/W4291020658","https://openalex.org/W2593813644"],"abstract_inverted_index":{"Topics":[0],"on":[1,81,179,224],"clustering":[2,13,19,49,58,69,78,92,127,144,226],"ensemble":[3,14,40,64,79,128,221],"have":[4],"attracted":[5],"much":[6],"attention":[7],"in":[8,116,142,167],"recent":[9],"years.":[10],"In":[11,120,146,208],"many":[12,66],"frameworks,":[15],"the":[16,22,29,43,53,56,63,77,91,107,112,117,149,159,164,168,180,189,211,216,219,230],"simple":[17],"partitional":[18,225],"methods,":[20],"e.g.,":[21,163],"most":[23],"famous":[24],"\u03ba-means,":[25],"are":[26,136,153,176],"used":[27,115,137],"as":[28],"ensemble's":[30],"member":[31,118,186],"\u201cclusterers\u201d,":[32],"due":[33],"to":[34,87,155],"their":[35,236],"low":[36,239],"computational":[37,240],"complexity.":[38],"These":[39],"approaches":[41,222],"extend":[42],"scope":[44],"of":[45,47,55,68,133,171,182,185,218,238],"application":[46],"individual":[48],"algorithms,":[50,227],"and":[51,188,228],"improve":[52],"robustness":[54],"final":[57],"results.":[59],"However,":[60],"by":[61,106],"applying":[62],"approaches,":[65],"problems":[67],"algorithms":[70],"still":[71,84],"cannot":[72],"be":[73,197],"settled.":[74],"For":[75],"example,":[76],"based":[80,178,223],"\u03ba-means":[82],"might":[83],"not":[85],"able":[86],"effectively":[88],"deal":[89,156],"with":[90,94,157,199],"tasks":[93],"arbitrary":[95],"clusters'":[96],"shapes":[97],"or":[98],"imbalanced":[99],"clusters's":[100],"sizes.":[101],"This":[102],"problem":[103],"is":[104],"caused":[105],"geometric-distance-based":[108],"closeness":[109,134,190,202],"measures":[110,135],"(e.g.":[111],"Euclidean":[113],"distance)":[114],"clusterers.":[119],"this":[121,147,209],"paper,":[122],"we":[123],"propose":[124],"a":[125,183,200],"multi-layer":[126],"framework":[129,213],"where":[130],"different":[131,139],"kinds":[132],"for":[138],"data":[140,150,161,165,194],"points":[141,151,166,195],"one":[143],"task.":[145],"framework,":[148],"which":[152],"hard":[154],"(called":[158],"\u201cbad":[160],"points\u201d,":[162],"\u201coverlapping\u201d":[169],"region":[170],"two":[172],"non-spherical":[173],"shaped":[174],"clusters)":[175],"identified":[177],"outputs":[181],"group":[184],"clusterers,":[187],"between":[191],"these":[192],"bad":[193],"will":[196],"calculated":[198],"non-geometric-distance-based":[201],"measure":[203],"called":[204],"C":[205],"M":[206],"NC.":[207],"way,":[210],"new":[212],"can":[214],"counter-act":[215],"drawbacks":[217],"traditional":[220],"at":[229],"same":[231],"time,":[232],"it":[233],"partially":[234],"retains":[235],"merits":[237],"cost.":[241]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
