{"id":"https://openalex.org/W4224315096","doi":"https://doi.org/10.1145/3485447.3511937","title":"Path Language Modeling over Knowledge Graphsfor Explainable Recommendation","display_name":"Path Language Modeling over Knowledge Graphsfor Explainable Recommendation","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4224315096","doi":"https://doi.org/10.1145/3485447.3511937"},"language":"en","primary_location":{"id":"doi:10.1145/3485447.3511937","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3511937","pdf_url":null,"source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-article"},"type":"conference-paper","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/A5080973846","display_name":"Shijie Geng","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shijie Geng","raw_affiliation_strings":["Rutgers University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017387871","display_name":"Zuohui Fu","orcid":"https://orcid.org/0000-0002-3881-7935"},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zuohui Fu","raw_affiliation_strings":["Meta Platforms, Inc., USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta Platforms, Inc., USA","institution_ids":["https://openalex.org/I4210114444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002064919","display_name":"Juntao Tan","orcid":"https://orcid.org/0000-0003-3646-933X"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Juntao Tan","raw_affiliation_strings":["Rutgers University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020526977","display_name":"Yingqiang Ge","orcid":"https://orcid.org/0000-0002-3736-2377"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingqiang Ge","raw_affiliation_strings":["Rutgers University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085818578","display_name":"Gerard de Melo","orcid":"https://orcid.org/0000-0002-2930-2059"},"institutions":[{"id":"https://openalex.org/I176453806","display_name":"University of Potsdam","ror":"https://ror.org/03bnmw459","country_code":"DE","type":"education","lineage":["https://openalex.org/I176453806"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gerard de Melo","raw_affiliation_strings":["HPI / University of Potsdam, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HPI / University of Potsdam, Germany","institution_ids":["https://openalex.org/I176453806"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100329828","display_name":"Yongfeng Zhang","orcid":"https://orcid.org/0000-0003-2633-8555"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yongfeng Zhang","raw_affiliation_strings":["Rutgers University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":79,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"946","last_page":"955"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9993000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7575782537460327},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.679522693157196},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.6678351163864136},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5704303979873657},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5426488518714905},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.5030755400657654},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4489428997039795},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4451283812522888},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4123263359069824},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4015805721282959},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39910152554512024},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3306071162223816},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10164210200309753},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08307218551635742},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08227911591529846}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7575782537460327},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.679522693157196},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.6678351163864136},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5704303979873657},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5426488518714905},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.5030755400657654},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4489428997039795},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4451283812522888},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4123263359069824},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4015805721282959},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39910152554512024},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3306071162223816},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10164210200309753},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08307218551635742},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08227911591529846},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"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":1,"locations":[{"id":"doi:10.1145/3485447.3511937","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3511937","pdf_url":null,"source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G1309303346","display_name":null,"funder_award_id":"IIS-1910154, IIS-2007907, IIS-2046457","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1554540371","https://openalex.org/W2046974451","https://openalex.org/W2152184085","https://openalex.org/W2294429012","https://openalex.org/W2337403844","https://openalex.org/W2509893387","https://openalex.org/W2743104969","https://openalex.org/W2781528640","https://openalex.org/W2792839191","https://openalex.org/W2798385737","https://openalex.org/W2810409598","https://openalex.org/W2945623882","https://openalex.org/W2950275995","https://openalex.org/W2950339735","https://openalex.org/W2952889708","https://openalex.org/W2962739339","https://openalex.org/W2962756421","https://openalex.org/W2964258748","https://openalex.org/W2970641574","https://openalex.org/W2998385486","https://openalex.org/W3024683329","https://openalex.org/W3029587262","https://openalex.org/W3034999214","https://openalex.org/W3035390927","https://openalex.org/W3035523484","https://openalex.org/W3093531652","https://openalex.org/W3093532296","https://openalex.org/W3098087397","https://openalex.org/W3102172133","https://openalex.org/W3102173443","https://openalex.org/W3134294468","https://openalex.org/W3153088333","https://openalex.org/W3172887316","https://openalex.org/W3176750236","https://openalex.org/W3207166518","https://openalex.org/W4205334834","https://openalex.org/W4206765718","https://openalex.org/W4238846128","https://openalex.org/W4250893105","https://openalex.org/W6774977730"],"related_works":["https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405","https://openalex.org/W2056712470","https://openalex.org/W3125580266","https://openalex.org/W4288390103","https://openalex.org/W2358294942","https://openalex.org/W4367460280"],"abstract_inverted_index":{"To":[0,107],"facilitate":[1],"human":[2],"decisions":[3],"with":[4],"credible":[5],"suggestions,":[6],"personalized":[7],"recommender":[8],"systems":[9],"should":[10],"have":[11],"the":[12,66,71,81,84,156,162,170,175,187,209,214],"ability":[13],"to":[14,35,164,181],"generate":[15],"corresponding":[16],"explanations":[17],"while":[18],"making":[19],"recommendations.":[20],"Knowledge":[21],"graphs":[22],"(KG),":[23],"which":[24],"contain":[25],"comprehensive":[26],"information":[27],"about":[28],"users":[29],"and":[30,64,130,139,145,199,211],"products,":[31],"are":[32,93],"widely":[33],"used":[34],"enable":[36],"this.":[37],"By":[38],"reasoning":[39],"over":[40,124],"a":[41,44,51,96,112,121,142,150,193],"KG":[42,86,105,125,166,188],"in":[43,99,141],"node-by-node":[45],"manner,":[46],"existing":[47,102],"explainable":[48,183],"models":[49],"provide":[50],"KG-grounded":[52],"path":[53,133],"for":[54],"each":[55],"user-recommended":[56],"item.":[57],"Such":[58],"paths":[59,126],"serve":[60],"as":[61],"an":[62],"explanation":[63,140],"reflect":[65],"historical":[67],"behavior":[68],"pattern":[69],"of":[70,101,104,128,196,213],"user.":[72],"However,":[73],"not":[74,153],"all":[75],"items":[76],"can":[77],"be":[78],"reached":[79],"following":[80],"connections":[82],"within":[83],"constructed":[85],"under":[87],"finite":[88],"hops.":[89],"Hence,":[90],"previous":[91],"approaches":[92],"constrained":[94],"by":[95],"recall":[97,172],"bias":[98],"terms":[100],"connectivity":[103],"structures.":[106],"overcome":[108],"this,":[109],"we":[110],"propose":[111],"novel":[113],"Path":[114],"Language":[115],"Modeling":[116],"Recommendation":[117],"(PLM-Rec)":[118],"framework,":[119],"learning":[120],"language":[122],"model":[123],"consisting":[127],"entities":[129],"edges.":[131],"Through":[132],"sequence":[134],"decoding,":[135],"PLM-Rec":[136,152,215],"unifies":[137],"recommendation":[138,184],"single":[143],"step":[144],"fulfills":[146],"them":[147],"simultaneously.":[148],"As":[149],"result,":[151],"only":[154],"captures":[155],"user":[157],"behaviors":[158],"but":[159],"also":[160],"eliminates":[161],"restriction":[163],"pre-existing":[165],"connections,":[167],"thereby":[168],"alleviating":[169],"aforementioned":[171],"bias.":[173],"Moreover,":[174],"proposed":[176],"technique":[177],"makes":[178],"it":[179],"possible":[180],"conduct":[182],"even":[185],"when":[186],"is":[189],"sparse":[190],"or":[191],"possesses":[192],"large":[194],"number":[195],"relations.":[197],"Experiments":[198],"extensive":[200],"ablation":[201],"studies":[202],"on":[203],"three":[204],"Amazon":[205],"e-commerce":[206],"datasets":[207],"demonstrate":[208],"effectiveness":[210],"explainability":[212],"framework.":[216]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":26},{"year":2022,"cited_by_count":8}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}