{"id":"https://openalex.org/W2011098209","doi":"https://doi.org/10.1109/iri.2014.7051959","title":"A proximity measure for link prediction in social user-item networks","display_name":"A proximity measure for link prediction in social user-item networks","publication_year":2014,"publication_date":"2014-08-01","ids":{"openalex":"https://openalex.org/W2011098209","doi":"https://doi.org/10.1109/iri.2014.7051959","mag":"2011098209"},"language":"en","primary_location":{"id":"doi:10.1109/iri.2014.7051959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iri.2014.7051959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014)","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/A5113569032","display_name":"Chun-Hao Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Chun-Hao Fu","raw_affiliation_strings":["Institute of Communications Engineering, National Tsing Hua University, Taiwan, R.O.C","Institute of Communications Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"Institute of Communications Engineering, National Tsing Hua University, Taiwan, R.O.C","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"Institute of Communications Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan, R.O.C","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016945609","display_name":"Cheng\u2010Shang Chang","orcid":"https://orcid.org/0000-0002-5386-4756"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Cheng-Shang Chang","raw_affiliation_strings":["Institute of Communications Engineering, National Tsing Hua University, Taiwan, R.O.C","Institute of Communications Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"Institute of Communications Engineering, National Tsing Hua University, Taiwan, R.O.C","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"Institute of Communications Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan, R.O.C","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043136272","display_name":"Duan\u2010Shin Lee","orcid":"https://orcid.org/0000-0003-4578-2002"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Duan-Shin Lee","raw_affiliation_strings":["Institute of Communications Engineering, National Tsing Hua University, Taiwan, R.O.C","Institute of Communications Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"Institute of Communications Engineering, National Tsing Hua University, Taiwan, R.O.C","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"Institute of Communications Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan, R.O.C","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5113569032"],"corresponding_institution_ids":["https://openalex.org/I25846049"],"apc_list":null,"apc_paid":null,"fwci":0.818,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.81884295,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"710","last_page":"717"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9987999796867371,"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":0.9983000159263611,"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":0.7561807036399841},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.6791666746139526},{"id":"https://openalex.org/keywords/random-walk","display_name":"Random walk","score":0.6068070530891418},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5901200771331787},{"id":"https://openalex.org/keywords/social-network","display_name":"Social network (sociolinguistics)","score":0.5216425061225891},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5163336992263794},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5017917156219482},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.4297488331794739},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42510661482810974},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41064226627349854},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3927934765815735},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3179190754890442},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.18719112873077393},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1462368369102478},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14465123414993286},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.12492352724075317},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.1196419894695282}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7561807036399841},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.6791666746139526},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.6068070530891418},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5901200771331787},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.5216425061225891},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5163336992263794},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5017917156219482},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.4297488331794739},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42510661482810974},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41064226627349854},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3927934765815735},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3179190754890442},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.18719112873077393},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1462368369102478},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14465123414993286},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.12492352724075317},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.1196419894695282},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iri.2014.7051959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iri.2014.7051959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.643.1121","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.643.1121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ee.nthu.edu.tw/cschang/paper16final.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5299999713897705}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W40442397","https://openalex.org/W103340358","https://openalex.org/W188608978","https://openalex.org/W229097380","https://openalex.org/W1533841329","https://openalex.org/W1539269997","https://openalex.org/W1815611020","https://openalex.org/W1864134408","https://openalex.org/W1966553486","https://openalex.org/W1983369859","https://openalex.org/W2026417691","https://openalex.org/W2028912620","https://openalex.org/W2037933327","https://openalex.org/W2039688703","https://openalex.org/W2040367556","https://openalex.org/W2056021151","https://openalex.org/W2066636486","https://openalex.org/W2070700141","https://openalex.org/W2071676926","https://openalex.org/W2079335968","https://openalex.org/W2083390547","https://openalex.org/W2084527756","https://openalex.org/W2100755716","https://openalex.org/W2110325612","https://openalex.org/W2117354486","https://openalex.org/W2119825970","https://openalex.org/W2121710227","https://openalex.org/W2130789338","https://openalex.org/W2144487656","https://openalex.org/W2146938438","https://openalex.org/W2147107544","https://openalex.org/W2159094788","https://openalex.org/W2164361866","https://openalex.org/W2165949563","https://openalex.org/W2538492099","https://openalex.org/W2745750801","https://openalex.org/W2950332743","https://openalex.org/W2950359222","https://openalex.org/W3122868618","https://openalex.org/W3133677217","https://openalex.org/W4232932184","https://openalex.org/W4244404635","https://openalex.org/W6608852248","https://openalex.org/W6632182941","https://openalex.org/W6646066776","https://openalex.org/W6676522543","https://openalex.org/W6790701681"],"related_works":["https://openalex.org/W2371352078","https://openalex.org/W2953461625","https://openalex.org/W2319693127","https://openalex.org/W2072263576","https://openalex.org/W2474567666","https://openalex.org/W1940044583","https://openalex.org/W2056226831","https://openalex.org/W2806903871","https://openalex.org/W2294667518","https://openalex.org/W4320802053"],"abstract_inverted_index":{"Recommendation":[0],"systems":[1],"based":[2,58],"on":[3,59,176],"historical":[4],"action":[5],"logs":[6],"between":[7,105],"users":[8],"and":[9,22,45,66,98,153],"items":[10],"are":[11],"usually":[12],"formulated":[13],"as":[14],"link":[15,55],"prediction":[16,56],"problems":[17,24],"for":[18,47,91],"user-item":[19,68,74,111],"bipartite":[20,69],"networks,":[21,38],"such":[23,92,115],"have":[25],"been":[26,80],"studied":[27],"extensively":[28],"in":[29,76,108,119,195],"the":[30,33,54,60,88,138,164,177,199],"literature.":[31],"With":[32,181],"advent":[34],"of":[35,62,87,197],"on-line":[36],"social":[37,39,64,73,110],"interactions":[40],"can":[41,155],"also":[42],"be":[43],"recorded":[44],"used":[46],"predicting":[48],"user's":[49],"future":[50],"actions.":[51],"As":[52],"such,":[53],"problem":[57,94],"union":[61],"a":[63,67,72,81,93,109,116,125,158,182],"network":[65,75],"network,":[70],"called":[71],"this":[77,120],"paper,":[78],"has":[79],"hot":[82],"research":[83],"topic":[84],"recently.":[85],"One":[86],"key":[89],"challenges":[90],"is":[95,144],"to":[96,146,150,157],"identify":[97],"compute":[99,114],"an":[100],"appropriate":[101],"proximity":[102,117,160],"(similarity)":[103],"measure":[104,161],"two":[106,129,165],"nodes":[107],"network.":[112],"To":[113,168],"measure,":[118],"paper":[121],"we":[122,172],"propose":[123],"using":[124],"random":[126,140,193],"walk":[127],"with":[128],"different":[130,134,148,151],"jumping":[131,166],"probabilities":[132],"toward":[133],"neighboring":[135],"nodes.":[136],"Unlike":[137],"simple":[139],"walk,":[141],"our":[142,170,187],"method":[143,188],"able":[145],"assign":[147],"weights":[149],"paths":[152],"thus":[154],"lead":[156],"better":[159,191],"by":[162],"optimizing":[163],"probabilities.":[167],"test":[169],"method,":[171],"conduct":[173],"various":[174],"experiments":[175],"DBLP":[178],"dataset":[179],"[21].":[180],"3-5":[183],"year":[184],"training":[185],"period,":[186],"performs":[189],"significantly":[190],"than":[192],"guess":[194],"terms":[196],"minimizing":[198],"root":[200],"mean":[201],"squared":[202],"error.":[203]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}