{"id":"https://openalex.org/W2533635416","doi":"https://doi.org/10.1145/2983323.2983754","title":"Collective Classification via Discriminative Matrix Factorization on Sparsely Labeled Networks","display_name":"Collective Classification via Discriminative Matrix Factorization on Sparsely Labeled Networks","publication_year":2016,"publication_date":"2016-10-24","ids":{"openalex":"https://openalex.org/W2533635416","doi":"https://doi.org/10.1145/2983323.2983754","mag":"2533635416"},"language":"en","primary_location":{"id":"doi:10.1145/2983323.2983754","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2983323.2983754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM International on Conference on Information and Knowledge Management","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/A5100438529","display_name":"Daokun Zhang","orcid":"https://orcid.org/0000-0002-1803-5768"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Daokun Zhang","raw_affiliation_strings":["University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014017635","display_name":"Jie Yin","orcid":"https://orcid.org/0000-0002-2063-8437"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"funder","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jie Yin","raw_affiliation_strings":["CSIRO, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"CSIRO, Sydney, Australia","institution_ids":["https://openalex.org/I1292875679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084641325","display_name":"Xingquan Zhu","orcid":"https://orcid.org/0000-0003-4129-9611"},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingquan Zhu","raw_affiliation_strings":["Florida Atlantic University, Boca Raton, USA"],"affiliations":[{"raw_affiliation_string":"Florida Atlantic University, Boca Raton, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100438525","display_name":"Chengqi Zhang","orcid":"https://orcid.org/0000-0001-5715-7154"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Chengqi Zhang","raw_affiliation_strings":["University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100438529"],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":7.0945,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.97058328,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1563","last_page":"1572"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9986000061035156,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9986000061035156,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9940999746322632,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7993828058242798},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.735467255115509},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6882660984992981},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.6520227193832397},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.48346811532974243},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4800663888454437},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47218480706214905},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4106519818305969},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34892499446868896},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34174469113349915},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.0700000524520874}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7993828058242798},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.735467255115509},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6882660984992981},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.6520227193832397},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.48346811532974243},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4800663888454437},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47218480706214905},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4106519818305969},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34892499446868896},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34174469113349915},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0700000524520874},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2983323.2983754","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2983323.2983754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM International on Conference on Information and Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/121826","is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/121826","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W36903255","https://openalex.org/W1488357069","https://openalex.org/W1497435662","https://openalex.org/W1888005072","https://openalex.org/W1971958549","https://openalex.org/W1972748503","https://openalex.org/W2010705340","https://openalex.org/W2046253692","https://openalex.org/W2099352187","https://openalex.org/W2100045227","https://openalex.org/W2121250409","https://openalex.org/W2153959628","https://openalex.org/W2154851992","https://openalex.org/W2161172169","https://openalex.org/W2187089797","https://openalex.org/W2242161203","https://openalex.org/W2950133940","https://openalex.org/W2952900479","https://openalex.org/W3104097132","https://openalex.org/W3105705953"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2521627374","https://openalex.org/W1588041347"],"abstract_inverted_index":{"We":[0],"address":[1],"the":[2,13,47,85,137,199,216],"problem":[3],"of":[4,34,136],"classifying":[5,183],"sparsely":[6,51,220],"labeled":[7,10,63,75,113,154,221],"networks,":[8],"where":[9],"nodes":[11,54,76,155],"in":[12,117],"network":[14,49,106,138,146,174],"are":[15],"extremely":[16],"scarce.":[17],"Existing":[18],"algorithms,":[19],"such":[20],"as":[21],"collective":[22,159],"classification,":[23],"have":[24,55],"been":[25],"shown":[26],"to":[27,62,70,77,119,127,131,156,197],"be":[28],"effective":[29],"for":[30,182],"jointly":[31],"deriving":[32],"labels":[33],"related":[35],"nodes,":[36,116],"by":[37,108],"exploiting":[38,109],"class":[39],"label":[40,80],"dependencies":[41],"among":[42],"neighboring":[43],"nodes.":[44,64],"However,":[45],"when":[46],"underlying":[48],"is":[50,126,195],"labeled,":[52],"most":[53],"too":[56],"few":[57],"or":[58],"even":[59],"no":[60],"connections":[61],"This":[65],"makes":[66],"it":[67],"very":[68],"difficult":[69],"leverage":[71],"supervised":[72],"knowledge":[73],"from":[74,153],"accurately":[78],"estimate":[79],"dependencies,":[81],"thereby":[82],"largely":[83],"degrading":[84],"classification":[86],"accuracy.":[87],"In":[88],"this":[89],"paper,":[90],"we":[91,164],"propose":[92],"a":[93,104,133,166],"novel":[94],"discriminative":[95,150],"matrix":[96,129,168],"factorization":[97,130,169],"(DMF)":[98],"based":[99,190],"algorithm":[100,189],"that":[101,139,172,209],"effectively":[102],"learns":[103],"latent":[105],"representation":[107,135,175],"topological":[110],"paths":[111],"between":[112],"and":[114,145,148],"unlabeled":[115],"addition":[118],"nodes'":[120,142],"content":[121,143],"information.":[122],"The":[123],"main":[124],"idea":[125],"use":[128],"obtain":[132],"compact":[134],"fully":[140],"encodes":[141],"information":[144],"structure,":[147],"unleash":[149],"power":[151],"inferred":[152],"directly":[157],"benefit":[158],"classification.":[160],"To":[161],"achieve":[162],"this,":[163],"formulate":[165],"new":[167,200],"objective":[170,201],"function":[171],"integrates":[173],"learning":[176],"with":[177],"an":[178],"empirical":[179],"loss":[180],"minimization":[181],"node":[184],"labels.":[185],"An":[186],"efficient":[187],"optimization":[188],"on":[191,205,219],"conjugate":[192],"gradient":[193],"methods":[194],"proposed":[196],"solve":[198],"function.":[202],"Experimental":[203],"results":[204],"real-world":[206],"networks":[207],"show":[208],"DMF":[210],"yields":[211],"superior":[212],"performance":[213],"gain":[214],"over":[215],"state-of-the-art":[217],"baselines":[218],"networks.":[222]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":4}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
