{"id":"https://openalex.org/W3094390815","doi":"https://doi.org/10.1145/3340531.3416021","title":"Graph Neural Network for Tag Ranking in Tag-enhanced Video Recommendation","display_name":"Graph Neural Network for Tag Ranking in Tag-enhanced Video Recommendation","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W3094390815","doi":"https://doi.org/10.1145/3340531.3416021","mag":"3094390815"},"language":"en","primary_location":{"id":"doi:10.1145/3340531.3416021","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3416021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information & 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/A5115061716","display_name":"Qi Liu","orcid":"https://orcid.org/0000-0002-4953-1537"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qi Liu","raw_affiliation_strings":["WeChat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"WeChat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101577090","display_name":"Ruobing Xie","orcid":"https://orcid.org/0000-0003-3170-5647"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruobing Xie","raw_affiliation_strings":["WeChat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"WeChat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333481","display_name":"Lei Chen","orcid":"https://orcid.org/0000-0002-5537-8989"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["WeChat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"WeChat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035078709","display_name":"Shukai Liu","orcid":"https://orcid.org/0000-0001-7369-2958"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shukai Liu","raw_affiliation_strings":["WeChat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"WeChat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062499743","display_name":"Ke Tu","orcid":"https://orcid.org/0009-0009-4922-1684"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Tu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009228005","display_name":"Peng Cui","orcid":"https://orcid.org/0000-0003-2957-8511"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Cui","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100335384","display_name":"Bo Zhang","orcid":"https://orcid.org/0000-0003-2942-1311"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Zhang","raw_affiliation_strings":["WeChat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"WeChat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023086553","display_name":"Leyu Lin","orcid":"https://orcid.org/0000-0001-5471-500X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leyu Lin","raw_affiliation_strings":["WeChat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"WeChat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5115061716"],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":8.8078,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.97841393,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2613","last_page":"2620"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T11478","display_name":"Caching and Content Delivery","score":0.958899974822998,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.8684462308883667},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6106761693954468},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.588760495185852},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5547821521759033},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5253987908363342},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4806060492992401},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.451566219329834},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.3799911141395569}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8684462308883667},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6106761693954468},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.588760495185852},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5547821521759033},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5253987908363342},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4806060492992401},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.451566219329834},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3799911141395569},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3340531.3416021","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3416021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information & Knowledge Management","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":34,"referenced_works":["https://openalex.org/W1553232534","https://openalex.org/W1665214252","https://openalex.org/W1990843604","https://openalex.org/W2018426558","https://openalex.org/W2040367556","https://openalex.org/W2089349245","https://openalex.org/W2154851992","https://openalex.org/W2295739661","https://openalex.org/W2519887557","https://openalex.org/W2567346959","https://openalex.org/W2598424083","https://openalex.org/W2604662567","https://openalex.org/W2624431344","https://openalex.org/W2789171794","https://openalex.org/W2894087624","https://openalex.org/W2898085636","https://openalex.org/W2899457523","https://openalex.org/W2911286998","https://openalex.org/W2913081710","https://openalex.org/W2914721378","https://openalex.org/W2941513815","https://openalex.org/W2941768562","https://openalex.org/W2951626319","https://openalex.org/W2963323306","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963858333","https://openalex.org/W2964121744","https://openalex.org/W2965857891","https://openalex.org/W3012871709","https://openalex.org/W3098203226","https://openalex.org/W3101704389","https://openalex.org/W3101707147","https://openalex.org/W3104097132"],"related_works":["https://openalex.org/W2468279273","https://openalex.org/W2354198838","https://openalex.org/W1989130879","https://openalex.org/W2103419012","https://openalex.org/W4390273403","https://openalex.org/W2988126442","https://openalex.org/W4386781444","https://openalex.org/W3092950680","https://openalex.org/W4246980185","https://openalex.org/W2150182025"],"abstract_inverted_index":{"In":[0,99,160],"tag-enhanced":[1,196],"video":[2,65,172,184,197],"recommendation":[3,24,173],"systems,":[4],"videos":[5,16,31],"are":[6,216],"attached":[7],"with":[8,119],"some":[9],"tags":[10,96],"that":[11,132],"highlight":[12],"the":[13,83,190],"contents":[14],"of":[15],"from":[17,32],"different":[18],"aspects.":[19],"Tag":[20],"ranking":[21,39,72,111],"in":[22,86,141,175,182,194,217],"such":[23],"systems":[25],"provides":[26],"personalized":[27],"tag":[28,34,38,51,61,71,110,186],"lists":[29],"for":[30,208],"their":[33,49],"candidates.":[35],"A":[36],"better":[37],"model":[40],"could":[41],"attract":[42],"users":[43],"to":[44,151],"click":[45,62],"more":[46,55,209],"tags,":[47],"enter":[48],"corresponding":[50],"channels,":[52],"and":[53,64,97,123,137,166,185,192],"watch":[54],"tag-specific":[56],"videos,":[57],"which":[58],"improves":[59],"both":[60,95,164,183],"rate":[63],"watching":[66],"time.":[67],"However,":[68],"most":[69],"conventional":[70],"models":[73],"merely":[74],"concentrate":[75],"on":[76,94,114,169,204],"tag-video":[77],"relevance":[78],"or":[79],"tag-related":[80],"behaviors,":[81],"ignoring":[82],"rich":[84],"information":[85],"video-related":[87],"behaviors.":[88],"We":[89,125,144],"should":[90],"consider":[91],"user":[92,122,154],"preferences":[93,155],"videos.":[98],"this":[100],"paper,":[101],"we":[102,162],"propose":[103,146],"a":[104,115,127,147,170],"novel":[105,128],"Graph":[106],"neural":[107,130,138],"network":[108,118,131],"based":[109,149],"(GraphTR)":[112],"framework":[113],"huge":[116],"heterogeneous":[117,157],"video,":[120],"tag,":[121],"media.":[124],"design":[126],"graph":[129],"combines":[133],"multi-field":[134],"transformer,":[135],"GraphSAGE":[136],"FM":[139],"layers":[140],"node":[142,158],"aggregation.":[143],"also":[145],"neighbor-similarity":[148],"loss":[150],"encode":[152],"various":[153],"into":[156],"representations.":[159],"experiments,":[161],"conduct":[163],"offline":[165],"online":[167],"evaluations":[168],"real-world":[171,195],"system":[174],"WeChat":[176,205],"Top":[177,206],"Stories.":[178],"The":[179,213],"significant":[180],"improvements":[181],"related":[187],"metrics":[188],"confirm":[189],"effectiveness":[191],"robustness":[193],"recommendation.":[198],"Currently,":[199],"GraphTR":[200],"has":[201],"been":[202],"deployed":[203],"Stories":[207],"than":[210],"six":[211],"months.":[212],"source":[214],"codes":[215],"https://github.com/lqfarmer/GraphTR.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}