{"id":"https://openalex.org/W2002163386","doi":"https://doi.org/10.1145/2487575.2487614","title":"Unsupervised link prediction using aggregative statistics on heterogeneous social networks","display_name":"Unsupervised link prediction using aggregative statistics on heterogeneous social networks","publication_year":2013,"publication_date":"2013-08-11","ids":{"openalex":"https://openalex.org/W2002163386","doi":"https://doi.org/10.1145/2487575.2487614","mag":"2002163386"},"language":"en","primary_location":{"id":"doi:10.1145/2487575.2487614","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2487575.2487614","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5046477105","display_name":"Tsung-Ting Kuo","orcid":"https://orcid.org/0000-0002-8728-4477"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Tsung-Ting Kuo","raw_affiliation_strings":["National Taiwan University, Taipei, Taiwan Roc","National Taiwan University, Taipei, Taiwan, ROC"],"affiliations":[{"raw_affiliation_string":"National Taiwan University, Taipei, Taiwan Roc","institution_ids":["https://openalex.org/I16733864"]},{"raw_affiliation_string":"National Taiwan University, Taipei, Taiwan, ROC","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100716372","display_name":"Rui Yan","orcid":"https://orcid.org/0000-0002-3356-6823"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Yan","raw_affiliation_strings":["Peking University, Peking, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Peking, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112240250","display_name":"Yu-Yang Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu-Yang Huang","raw_affiliation_strings":["National Taiwan University, Taipei, Taiwan Roc","National Taiwan University, Taipei, Taiwan, ROC"],"affiliations":[{"raw_affiliation_string":"National Taiwan University, Taipei, Taiwan Roc","institution_ids":["https://openalex.org/I16733864"]},{"raw_affiliation_string":"National Taiwan University, Taipei, Taiwan, ROC","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048739317","display_name":"Perng-Hwa Kung","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Perng-Hwa Kung","raw_affiliation_strings":["National Taiwan University, Taipei, Taiwan Roc","National Taiwan University, Taipei, Taiwan, ROC"],"affiliations":[{"raw_affiliation_string":"National Taiwan University, Taipei, Taiwan Roc","institution_ids":["https://openalex.org/I16733864"]},{"raw_affiliation_string":"National Taiwan University, Taipei, Taiwan, ROC","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087480257","display_name":"Shou-De Lin","orcid":"https://orcid.org/0000-0001-9970-1250"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shou-De Lin","raw_affiliation_strings":["National Taiwan University, Taipei, Taiwan Roc","National Taiwan University, Taipei, Taiwan, ROC"],"affiliations":[{"raw_affiliation_string":"National Taiwan University, Taipei, Taiwan Roc","institution_ids":["https://openalex.org/I16733864"]},{"raw_affiliation_string":"National Taiwan University, Taipei, Taiwan, ROC","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5046477105"],"corresponding_institution_ids":["https://openalex.org/I16733864"],"apc_list":null,"apc_paid":null,"fwci":5.7315,"has_fulltext":false,"cited_by_count":55,"citation_normalized_percentile":{"value":0.96238669,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"775","last_page":"783"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9915000200271606,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.829155445098877},{"id":"https://openalex.org/keywords/competitor-analysis","display_name":"Competitor analysis","score":0.7092553377151489},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6473892331123352},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.608879804611206},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5919398069381714},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.545415997505188},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5111280083656311},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5068262219429016},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5028318762779236},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.4757152199745178},{"id":"https://openalex.org/keywords/social-network","display_name":"Social network (sociolinguistics)","score":0.42311325669288635},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38087835907936096},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.19197550415992737},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.14130589365959167},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.1312461793422699}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.829155445098877},{"id":"https://openalex.org/C127576917","wikidata":"https://www.wikidata.org/wiki/Q624630","display_name":"Competitor analysis","level":2,"score":0.7092553377151489},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6473892331123352},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.608879804611206},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5919398069381714},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.545415997505188},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5111280083656311},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5068262219429016},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5028318762779236},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.4757152199745178},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.42311325669288635},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38087835907936096},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.19197550415992737},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.14130589365959167},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.1312461793422699},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2487575.2487614","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2487575.2487614","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.700.3551","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.700.3551","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ruiyan.me/pubs/KDD2013.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.41999998688697815}],"awards":[],"funders":[{"id":"https://openalex.org/F4320307102","display_name":"Intel Corporation","ror":"https://ror.org/01ek73717"},{"id":"https://openalex.org/F4320321040","display_name":"National Science Council","ror":"https://ror.org/02kv4zf79"},{"id":"https://openalex.org/F4320323900","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W170896097","https://openalex.org/W758960492","https://openalex.org/W958171979","https://openalex.org/W1503428008","https://openalex.org/W1943015726","https://openalex.org/W1964731129","https://openalex.org/W1970429620","https://openalex.org/W1976526581","https://openalex.org/W1978558026","https://openalex.org/W1979104937","https://openalex.org/W2004858782","https://openalex.org/W2021515354","https://openalex.org/W2021579368","https://openalex.org/W2022322548","https://openalex.org/W2022867359","https://openalex.org/W2037933327","https://openalex.org/W2069870183","https://openalex.org/W2073415627","https://openalex.org/W2087692915","https://openalex.org/W2105644991","https://openalex.org/W2105842272","https://openalex.org/W2117764127","https://openalex.org/W2127267264","https://openalex.org/W2127430306","https://openalex.org/W2137793309","https://openalex.org/W2137813581","https://openalex.org/W2148847267","https://openalex.org/W2155186673","https://openalex.org/W2159080219","https://openalex.org/W2167467982","https://openalex.org/W2265862919","https://openalex.org/W2406950355","https://openalex.org/W2534696358","https://openalex.org/W3010318089","https://openalex.org/W3020913839"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W4387073571"],"abstract_inverted_index":{"The":[0,173],"concern":[1],"of":[2,35,105],"privacy":[3],"has":[4],"become":[5],"an":[6,22],"important":[7],"issue":[8],"for":[9],"online":[10],"social":[11,62],"networks.":[12],"In":[13],"services":[14],"such":[15],"as":[16,147],"Foursquare.com,":[17],"whether":[18],"a":[19,51,60,74,84,97,109],"person":[20],"likes":[21],"article":[23],"is":[24,44],"considered":[25],"private":[26],"and":[27,102,112,134,165],"therefore":[28],"not":[29,151],"disclosed;":[30],"only":[31,152],"the":[32,56,160,170],"aggregative":[33,78],"statistics":[34,79],"articles":[36],"(i.e.,":[37],"how":[38],"many":[39],"people":[40],"like":[41],"this":[42,90,145],"article)":[43],"revealed.":[45],"This":[46,68,81],"paper":[47,82],"tries":[48],"to":[49,73,88,143],"answer":[50],"question:":[52],"can":[53,70],"we":[54,116],"predict":[55],"opinion":[57],"holder":[58],"in":[59,155],"heterogeneous":[61],"network":[63],"without":[64],"any":[65],"labeled":[66],"data?":[67],"question":[69],"be":[71],"generalized":[72],"link":[75],"prediction":[76,123],"with":[77],"problem.":[80],"devises":[83],"novel":[85],"unsupervised":[86,141],"framework":[87],"solve":[89,144],"problem,":[91],"including":[92],"two":[93],"main":[94],"components:":[95],"(1)":[96],"three-layer":[98],"factor":[99],"graph":[100],"model":[101],"three":[103],"types":[104],"potential":[106],"functions;":[107],"(2)":[108],"ranked-margin":[110],"learning":[111],"inference":[113],"algorithm.":[114],"Finally,":[115],"evaluate":[117],"our":[118],"method":[119],"on":[120,159],"four":[121,126],"diverse":[122],"scenarios":[124],"using":[125],"datasets:":[127],"preference":[128],"(Foursquare),":[129],"repost":[130],"(Twitter),":[131],"response":[132],"(Plurk),":[133],"citation":[135],"(DBLP).":[136],"We":[137],"further":[138],"exploit":[139],"nine":[140],"models":[142],"problem":[146],"baselines.":[148],"Our":[149],"approach":[150],"wins":[153],"out":[154],"all":[156],"scenarios,":[157],"but":[158],"average":[161],"achieves":[162],"9.90%":[163],"AUC":[164],"12.59%":[166],"NDCG":[167],"improvement":[168],"over":[169],"best":[171],"competitors.":[172],"resources":[174],"are":[175],"available":[176],"at":[177],"http://www.csie.ntu.edu.tw/~d97944007/aggregative/":[178]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}