{"id":"https://openalex.org/W3193441787","doi":"https://doi.org/10.1145/3459637.3482092","title":"DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNN","display_name":"DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNN","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3193441787","doi":"https://doi.org/10.1145/3459637.3482092","mag":"3193441787"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482092","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482092","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2108.11883","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112861905","display_name":"Yu Wang","orcid":"https://orcid.org/0000-0002-2792-3353"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yu Wang","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100321247","display_name":"Zhiwei Liu","orcid":"https://orcid.org/0000-0003-1525-1067"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiwei Liu","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017213607","display_name":"Ziwei Fan","orcid":"https://orcid.org/0000-0001-5445-2203"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ziwei Fan","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015105117","display_name":"Lichao Sun","orcid":"https://orcid.org/0000-0003-1539-7939"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lichao Sun","raw_affiliation_strings":["Lehigh University, Bethlehem, PA, USA"],"affiliations":[{"raw_affiliation_string":"Lehigh University, Bethlehem, PA, USA","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036357902","display_name":"Philip S. Yu","orcid":"https://orcid.org/0000-0002-3491-5968"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip S. Yu","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5112861905"],"corresponding_institution_ids":["https://openalex.org/I39422238"],"apc_list":null,"apc_paid":null,"fwci":11.6381,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.9847306,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3513","last_page":"3517"},"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":0.9995999932289124,"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":0.9815999865531921,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8235859870910645},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.799888014793396},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.7434933185577393},{"id":"https://openalex.org/keywords/rss","display_name":"RSS","score":0.6703482270240784},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5100570321083069},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.50362628698349},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4878065884113312},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.4362134337425232},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.4264862835407257},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3573097586631775},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34862780570983887},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.2578911781311035},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.09089097380638123},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07964038848876953}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8235859870910645},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.799888014793396},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.7434933185577393},{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.6703482270240784},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5100570321083069},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.50362628698349},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4878065884113312},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.4362134337425232},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.4264862835407257},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3573097586631775},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34862780570983887},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2578911781311035},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.09089097380638123},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07964038848876953},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3459637.3482092","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482092","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2108.11883","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2108.11883","pdf_url":"https://arxiv.org/pdf/2108.11883","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2108.11883","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2108.11883","pdf_url":"https://arxiv.org/pdf/2108.11883","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W2000042664","https://openalex.org/W2140310134","https://openalex.org/W2519887557","https://openalex.org/W2547875792","https://openalex.org/W2591957553","https://openalex.org/W2605350416","https://openalex.org/W2624431344","https://openalex.org/W2766453196","https://openalex.org/W2784814091","https://openalex.org/W2792839191","https://openalex.org/W2801992635","https://openalex.org/W2804057010","https://openalex.org/W2899374860","https://openalex.org/W2911286998","https://openalex.org/W2913560138","https://openalex.org/W2945623882","https://openalex.org/W2945827670","https://openalex.org/W2947798871","https://openalex.org/W2950975304","https://openalex.org/W2955162038","https://openalex.org/W2961295589","https://openalex.org/W2963601856","https://openalex.org/W2963911286","https://openalex.org/W2964015378","https://openalex.org/W2964051675","https://openalex.org/W2964114465","https://openalex.org/W2964554227","https://openalex.org/W2983466427","https://openalex.org/W2996268457","https://openalex.org/W2999269676","https://openalex.org/W3001487403","https://openalex.org/W3008933340","https://openalex.org/W3011809564","https://openalex.org/W3027812936","https://openalex.org/W3031029974","https://openalex.org/W3089060322","https://openalex.org/W3098087397","https://openalex.org/W3100278010","https://openalex.org/W3103362336","https://openalex.org/W3104353018","https://openalex.org/W3105636565","https://openalex.org/W3106439716","https://openalex.org/W3106445281","https://openalex.org/W3155936517","https://openalex.org/W3156977692","https://openalex.org/W3158237717","https://openalex.org/W3158371160","https://openalex.org/W3169632866","https://openalex.org/W3176750236","https://openalex.org/W3186065747","https://openalex.org/W3209048663","https://openalex.org/W3210802119","https://openalex.org/W4285719527","https://openalex.org/W4285723986","https://openalex.org/W4287025196","https://openalex.org/W4287120780","https://openalex.org/W4288022804","https://openalex.org/W4294558607","https://openalex.org/W6600351811"],"related_works":["https://openalex.org/W426968574","https://openalex.org/W2365639220","https://openalex.org/W2382520895","https://openalex.org/W2393709043","https://openalex.org/W2080567403","https://openalex.org/W2539387137","https://openalex.org/W2374952201","https://openalex.org/W2374808384","https://openalex.org/W2385449752","https://openalex.org/W3177075132"],"abstract_inverted_index":{"In":[0],"the":[1,24,44,84,109,119],"information":[2],"explosion":[3],"era,":[4],"recommender":[5,133],"systems":[6],"(RSs)":[7],"are":[8,51,60],"widely":[9],"studied":[10],"and":[11,53,92],"applied":[12],"to":[13,114],"discover":[14],"user-preferred":[15],"information.":[16,38],"A":[17],"RS":[18],"performs":[19],"poorly":[20],"when":[21],"suffering":[22],"from":[23,90],"cold-start":[25],"issue,":[26],"which":[27,107],"can":[28],"be":[29,115],"alleviated":[30],"if":[31],"incorporating":[32],"Knowledge":[33,74],"Graphs":[34],"(KGs)":[35],"as":[36],"side":[37],"However,":[39],"most":[40],"existing":[41],"works":[42],"neglect":[43],"facts":[45],"that":[46,82,127],"node":[47],"degrees":[48],"in":[49,58,66],"KGs":[50,59,91],"skewed":[52],"massive":[54],"amount":[55],"of":[56,87,111],"interactions":[57],"recommendation-irrelevant.":[61],"To":[62],"address":[63],"these":[64],"problems,":[65],"this":[67,99],"paper,":[68],"we":[69],"propose":[70],"Differentiable":[71],"Sampling":[72],"on":[73],"Graph":[75],"for":[76,96],"Recommendation":[77],"with":[78,118],"Relational":[79],"GNN":[80],"(DSKReG)":[81],"learns":[83],"relevance":[85],"distribution":[86],"connected":[88],"items":[89,95,113],"samples":[93],"suitable":[94],"recommendation":[97],"following":[98],"distribution.":[100],"We":[101],"devise":[102],"a":[103],"differentiable":[104],"sampling":[105],"strategy,":[106],"enables":[108],"selection":[110],"relevant":[112],"jointly":[116],"optimized":[117],"model":[120,129],"training":[121],"procedure.":[122],"The":[123,135],"experimental":[124],"results":[125],"demonstrate":[126],"our":[128],"outperforms":[130],"state-of-the-art":[131],"KG-based":[132],"systems.":[134],"code":[136],"is":[137],"available":[138],"online":[139],"at":[140],"https://github.com/YuWang-1024/DSKReG.":[141]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":5}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2021-08-30T00:00:00"}
