{"id":"https://openalex.org/W3012705926","doi":"https://doi.org/10.1145/3366423.3380077","title":"Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction","display_name":"Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction","publication_year":2020,"publication_date":"2020-04-20","ids":{"openalex":"https://openalex.org/W3012705926","doi":"https://doi.org/10.1145/3366423.3380077","mag":"3012705926"},"language":"en","primary_location":{"id":"doi:10.1145/3366423.3380077","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3380077","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The Web Conference 2020","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3366423.3380077","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100396372","display_name":"Wen Wang","orcid":"https://orcid.org/0000-0002-7801-2066"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wen Wang","raw_affiliation_strings":["East China Normal University"],"affiliations":[{"raw_affiliation_string":"East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101541045","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0001-6763-8146"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["East China Normal University"],"affiliations":[{"raw_affiliation_string":"East China Normal University","institution_ids":["https://openalex.org/I66867065"]}]},{"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":["Search Product Center WeChat Search Application Department Tencent"],"affiliations":[{"raw_affiliation_string":"Search Product Center WeChat Search Application Department Tencent","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","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":false,"raw_author_name":"Qi Liu","raw_affiliation_strings":["Search Product Center WeChat Search Application Department Tencent"],"affiliations":[{"raw_affiliation_string":"Search Product Center WeChat Search Application Department Tencent","institution_ids":["https://openalex.org/I2250653659"]}]},{"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":["Search Product Center WeChat Search Application Department Tencent"],"affiliations":[{"raw_affiliation_string":"Search Product Center WeChat Search Application Department Tencent","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","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":["Search Product Center WeChat Search Application Department Tencent"],"affiliations":[{"raw_affiliation_string":"Search Product Center WeChat Search Application Department Tencent","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046703129","display_name":"Hongyuan Zha","orcid":"https://orcid.org/0000-0001-7493-0911"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongyuan Zha","raw_affiliation_strings":["Georgia Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100396372"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":21.3522,"has_fulltext":false,"cited_by_count":118,"citation_normalized_percentile":{"value":0.99391442,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3056","last_page":"3062"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9943000078201294,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9789000153541565,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7490447163581848},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7185367345809937},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.6186096668243408},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5855627059936523},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4900285005569458},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4743053913116455},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4721524715423584},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.27811700105667114}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7490447163581848},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7185367345809937},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.6186096668243408},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5855627059936523},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4900285005569458},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4743053913116455},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4721524715423584},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27811700105667114},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"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:10.1145/3366423.3380077","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3380077","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The Web Conference 2020","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3366423.3380077","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3380077","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The Web Conference 2020","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1806220264","https://openalex.org/W1888005072","https://openalex.org/W2042281163","https://openalex.org/W2054141820","https://openalex.org/W2059512502","https://openalex.org/W2064754513","https://openalex.org/W2154851992","https://openalex.org/W2171279286","https://openalex.org/W2468907370","https://openalex.org/W2469952266","https://openalex.org/W2517217469","https://openalex.org/W2546696630","https://openalex.org/W2624431344","https://openalex.org/W2625746539","https://openalex.org/W2808446163","https://openalex.org/W2809307135","https://openalex.org/W2899457523","https://openalex.org/W2911946608","https://openalex.org/W2950133940","https://openalex.org/W2951369132","https://openalex.org/W2963043672","https://openalex.org/W2963669159","https://openalex.org/W2964926209","https://openalex.org/W2965857891","https://openalex.org/W2984100107","https://openalex.org/W3098231197","https://openalex.org/W3101707147","https://openalex.org/W3104097132","https://openalex.org/W3105705953"],"related_works":["https://openalex.org/W2468279273","https://openalex.org/W2354198838","https://openalex.org/W1989130879","https://openalex.org/W2103419012","https://openalex.org/W4296749040","https://openalex.org/W4230197055","https://openalex.org/W621808327","https://openalex.org/W644007644","https://openalex.org/W3012257603","https://openalex.org/W3177475962"],"abstract_inverted_index":{"Session-based":[0,128],"target":[1,77,129,153,173,198],"behavior":[2,15,24,56,66,78,99,130,147,156,176,225],"prediction":[3,25,217],"aims":[4],"to":[5,10,31,107,187],"predict":[6],"the":[7,51,61,76,180,208,220],"next":[8,194],"item":[9,195],"be":[11],"interacted":[12,196],"with":[13,197,214],"specific":[14],"types":[16],"(e.g.,":[17,83],"clicking).":[18],"Although":[19],"existing":[20],"methods":[21],"for":[22,57,127,134,192],"session-based":[23,216],"leverage":[26],"powerful":[27],"representation":[28],"learning":[29,227],"approaches":[30],"encode":[32,109],"items\u2019":[33],"sequential":[34],"relevance":[35],"in":[36,97],"a":[37,104,120,139,184],"low-dimensional":[38],"space,":[39],"they":[40,46,102],"suffer":[41],"from":[42,149],"several":[43],"limitations.":[44],"Firstly,":[45],"focus":[47],"on":[48,145,159,203],"only":[49],"utilizing":[50],"same":[52],"type":[53],"of":[54,63,210,222],"user":[55,169,190],"prediction,":[58],"but":[59,81],"ignore":[60],"potential":[62],"taking":[64],"other":[65],"data":[67],"as":[68],"auxiliary":[69,155,175,224],"information.":[70],"This":[71],"is":[72,79],"particularly":[73],"crucial":[74],"when":[75],"sparse":[80],"important":[82],"buying":[84],"or":[85],"sharing":[86],"an":[87],"item).":[88],"Secondly,":[89],"item-to-item":[90,164,228],"relations":[91,111,165,229],"are":[92],"modeled":[93],"separately":[94],"and":[95,101,154,166,174,226],"locally":[96],"one":[98],"sequence,":[100],"lack":[103],"principled":[105],"way":[106],"globally":[108],"these":[110,116],"more":[112],"effectively.":[113],"To":[114],"overcome":[115],"limitations,":[117],"we":[118,137],"propose":[119],"novel":[121],"Multi-relational":[122],"Graph":[123,142],"Neural":[124],"Network":[125],"model":[126],"Prediction,":[131],"namely":[132],"MGNN-SPred":[133,161,182,211],"short.":[135],"Specifically,":[136],"build":[138],"Multi-Relational":[140],"Item":[141],"(MRIG)":[143],"based":[144],"all":[146,150],"sequences":[148],"sessions,":[151],"involving":[152],"types.":[157],"Based":[158],"MRIG,":[160],"learns":[162],"global":[163],"further":[167],"obtains":[168],"preferences":[170],"w.r.t.":[171],"current":[172],"sequences,":[177],"respectively.":[178],"In":[179],"end,":[181],"leverages":[183],"gating":[185],"mechanism":[186],"adaptively":[188],"fuse":[189],"representations":[191],"predicting":[193],"behavior.":[199],"The":[200],"extensive":[201],"experiments":[202],"two":[204],"real-world":[205],"datasets":[206],"demonstrate":[207],"superiority":[209],"by":[212],"comparing":[213],"state-of-the-art":[215],"methods,":[218],"validating":[219],"benefits":[221],"leveraging":[223],"over":[230],"MRIG.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":26},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":26},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}