{"id":"https://openalex.org/W2402923626","doi":"https://doi.org/10.1137/1.9781611972832.14","title":"Evolutionary Soft Co-Clustering","display_name":"Evolutionary Soft Co-Clustering","publication_year":2013,"publication_date":"2013-05-02","ids":{"openalex":"https://openalex.org/W2402923626","doi":"https://doi.org/10.1137/1.9781611972832.14","mag":"2402923626"},"language":"en","primary_location":{"id":"doi:10.1137/1.9781611972832.14","is_oa":false,"landing_page_url":"https://doi.org/10.1137/1.9781611972832.14","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 SIAM International Conference on Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101552798","display_name":"Wenlu Zhang","orcid":"https://orcid.org/0000-0003-1973-6037"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenlu Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052278550","display_name":"Shuiwang Ji","orcid":"https://orcid.org/0000-0002-4205-4563"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuiwang Ji","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100421978","display_name":"Rui Zhang","orcid":"https://orcid.org/0000-0001-9418-0863"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rui Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3836,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.83282767,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"121","last_page":"129"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9969000220298767,"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/T10885","display_name":"Gene expression and cancer classification","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7962140440940857},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.7409626245498657},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6982205510139465},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.4809398055076599},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.4686526656150818},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4535738229751587},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4405451714992523},{"id":"https://openalex.org/keywords/biclustering","display_name":"Biclustering","score":0.4117480218410492},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3673042058944702},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3277828097343445},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.3142247796058655},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.29839593172073364}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7962140440940857},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7409626245498657},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6982205510139465},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.4809398055076599},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.4686526656150818},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4535738229751587},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4405451714992523},{"id":"https://openalex.org/C144817290","wikidata":"https://www.wikidata.org/wiki/Q2976575","display_name":"Biclustering","level":5,"score":0.4117480218410492},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3673042058944702},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3277828097343445},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.3142247796058655},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.29839593172073364}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/1.9781611972832.14","is_oa":false,"landing_page_url":"https://doi.org/10.1137/1.9781611972832.14","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 SIAM International Conference on Data Mining","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":31,"referenced_works":["https://openalex.org/W1493217831","https://openalex.org/W1578099820","https://openalex.org/W1598534305","https://openalex.org/W1902027874","https://openalex.org/W1981745143","https://openalex.org/W1985796418","https://openalex.org/W1986007546","https://openalex.org/W1992419399","https://openalex.org/W1998819761","https://openalex.org/W2007516075","https://openalex.org/W2036328877","https://openalex.org/W2040466507","https://openalex.org/W2052819443","https://openalex.org/W2108614537","https://openalex.org/W2113284213","https://openalex.org/W2121947440","https://openalex.org/W2129116669","https://openalex.org/W2130158951","https://openalex.org/W2132914434","https://openalex.org/W2133576408","https://openalex.org/W2141465109","https://openalex.org/W2144544802","https://openalex.org/W2146058975","https://openalex.org/W2153362134","https://openalex.org/W2154946202","https://openalex.org/W2155640700","https://openalex.org/W2165874743","https://openalex.org/W2170936641","https://openalex.org/W2198602317","https://openalex.org/W2293546752","https://openalex.org/W2434205482"],"related_works":["https://openalex.org/W1974340769","https://openalex.org/W2900595096","https://openalex.org/W4289277241","https://openalex.org/W2979322793","https://openalex.org/W2765801824","https://openalex.org/W2188068678","https://openalex.org/W2157302779","https://openalex.org/W1979094538","https://openalex.org/W3161541212","https://openalex.org/W2513650705"],"abstract_inverted_index":{"We":[0,73,118],"consider":[1],"the":[2,19,48,60,65,88,102,110,120],"mining":[3],"of":[4,87,104],"hidden":[5],"block":[6],"structures":[7],"from":[8],"time-varying":[9],"data":[10,50,128],"using":[11],"evolutionary":[12,38,115],"co-clustering.":[13,117],"Existing":[14],"methods":[15],"are":[16,51],"based":[17,140],"on":[18,59,123,141],"spectral":[20,142],"learning":[21],"framework,":[22],"thus":[23],"lacking":[24],"a":[25,34,54,69],"probabilistic":[26,35,90],"interpretation.":[27],"To":[28,101],"overcome":[29],"this":[30,41],"limitation,":[31],"we":[32],"develop":[33,74],"model":[36,45,91],"for":[37],"co-clustering":[39,98],"in":[40,68],"paper.":[42],"The":[43],"proposed":[44,89,121],"assumes":[46],"that":[47,57,93,133],"observed":[49],"generated":[52],"via":[53],"two-step":[55],"process":[56],"depends":[58],"historic":[61],"co-clusters,":[62],"thereby":[63],"capturing":[64],"temporal":[66],"smoothness":[67],"probabilistically":[70],"principled":[71],"manner.":[72],"an":[75],"EM":[76],"algorithm":[77],"to":[78,96,113],"perform":[79,114],"maximum":[80],"likelihood":[81],"parameter":[82],"estimation.":[83],"An":[84],"appealing":[85],"feature":[86],"is":[92],"it":[94],"leads":[95],"soft":[97,116],"assignments":[99],"naturally.":[100],"best":[103],"our":[105,107,134],"knowledge,":[106],"work":[108],"represents":[109],"first":[111],"attempt":[112],"evaluate":[119],"method":[122,135],"both":[124],"synthetic":[125],"and":[126],"real":[127],"sets.":[129],"Experimental":[130],"results":[131],"show":[132],"consistently":[136],"outperforms":[137],"prior":[138],"approaches":[139],"method.":[143]},"counts_by_year":[{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
