{"id":"https://openalex.org/W3080152140","doi":"https://doi.org/10.1145/3394486.3403050","title":"An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph","display_name":"An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph","publication_year":2020,"publication_date":"2020-08-20","ids":{"openalex":"https://openalex.org/W3080152140","doi":"https://doi.org/10.1145/3394486.3403050","mag":"3080152140"},"language":"en","primary_location":{"id":"doi:10.1145/3394486.3403050","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403050","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","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/A5035163745","display_name":"Jiarui Jin","orcid":"https://orcid.org/0000-0001-6458-1586"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiarui Jin","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060200431","display_name":"Jiarui Qin","orcid":"https://orcid.org/0000-0002-9064-885X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiarui Qin","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101552118","display_name":"Yuchen Fang","orcid":"https://orcid.org/0000-0002-7882-8698"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuchen Fang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074618552","display_name":"Kounianhua Du","orcid":"https://orcid.org/0000-0002-2611-5055"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kounianhua Du","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090720315","display_name":"Weinan Zhang","orcid":"https://orcid.org/0000-0002-0127-2425"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weinan Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001571390","display_name":"Yong Yu","orcid":"https://orcid.org/0000-0003-0281-8271"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Yu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100459168","display_name":"Zheng Zhang","orcid":"https://orcid.org/0000-0003-1470-6998"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng Zhang","raw_affiliation_strings":["Amazon Web Services, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Amazon Web Services, Shanghai, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000245150","display_name":"Alexander J. Smola","orcid":"https://orcid.org/0000-0002-7963-4721"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander J. Smola","raw_affiliation_strings":["Amazon Web Services, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Amazon Web Services, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I1311688040"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5035163745"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":22.253,"has_fulltext":false,"cited_by_count":114,"citation_normalized_percentile":{"value":0.99424435,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"75","last_page":"84"},"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":0.9998999834060669,"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/T11478","display_name":"Caching and Content Delivery","score":0.9921000003814697,"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":0.8345050811767578},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5797229409217834},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.568233072757721},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5334123969078064},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5071313381195068},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4319007694721222},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.427212119102478},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3693268597126007},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33156198263168335}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8345050811767578},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5797229409217834},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.568233072757721},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5334123969078064},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5071313381195068},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4319007694721222},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.427212119102478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3693268597126007},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33156198263168335}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394486.3403050","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403050","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W103340358","https://openalex.org/W1888005072","https://openalex.org/W2047729491","https://openalex.org/W2054141820","https://openalex.org/W2070700141","https://openalex.org/W2083381833","https://openalex.org/W2095054612","https://openalex.org/W2154851992","https://openalex.org/W2164259805","https://openalex.org/W2393319904","https://openalex.org/W2577283662","https://openalex.org/W2583803680","https://openalex.org/W2584620251","https://openalex.org/W2604662567","https://openalex.org/W2605350416","https://openalex.org/W2743104969","https://openalex.org/W2767774008","https://openalex.org/W2789042518","https://openalex.org/W2808844541","https://openalex.org/W2897676029","https://openalex.org/W2911286998","https://openalex.org/W2962756421","https://openalex.org/W2965857891","https://openalex.org/W3101444938","https://openalex.org/W3104097132","https://openalex.org/W3105705953"],"related_works":["https://openalex.org/W4206028705","https://openalex.org/W2604454537","https://openalex.org/W2808284704","https://openalex.org/W2883748392","https://openalex.org/W2757431232","https://openalex.org/W2954554213","https://openalex.org/W3200431764","https://openalex.org/W4288286922","https://openalex.org/W4206547516","https://openalex.org/W4293236197"],"abstract_inverted_index":{"There":[0],"is":[1,17,237],"an":[2,129,138,242],"influx":[3],"of":[4,19,85,156,175,218,225,233],"heterogeneous":[5,99,219],"information":[6,109],"network":[7,100],"(HIN)":[8],"based":[9],"recommender":[10],"systems":[11],"in":[12,119,159,200,247],"recent":[13],"years":[14],"since":[15,75],"HIN":[16],"capable":[18],"characterizing":[20],"complex":[21,184],"graphs":[22,220],"and":[23,62,73,82,161,188,204],"contains":[24],"rich":[25,123],"semantics.":[26],"Although":[27],"the":[28,40,89,122,154,169,191,222,231,238,248],"existing":[29,47],"approaches":[30],"have":[31],"achieved":[32],"performance":[33,223],"improvement,":[34],"while":[35],"practical,":[36],"they":[37],"still":[38],"face":[39],"following":[41],"problems.":[42,149],"On":[43,88],"one":[44],"hand,":[45,91],"most":[46],"HIN-based":[48,249],"methods":[49,68,94],"rely":[50],"on":[51,194,214],"explicit":[52],"path":[53,76],"reachability":[54],"to":[55,71,96,146,167,182],"leverage":[56],"path-based":[57],"semantic":[58],"relatedness":[59],"between":[60,172,186],"users":[61],"items,":[63],"e.g.,":[64],"metapath-based":[65],"similarities.":[66],"These":[67],"are":[69,78,83],"hard":[70],"use":[72],"integrate":[74],"connections":[77],"sparse":[79],"or":[80],"noisy,":[81],"often":[84],"different":[86,216],"lengths.":[87],"other":[90,92],"graph-based":[93],"aim":[95],"learn":[97,205],"effective":[98],"representations":[101],"by":[102],"compressing":[103],"node":[104],"together":[105],"with":[106,190,207,228],"its":[107],"neighborhood":[108],"into":[110],"single":[111],"embedding":[112],"before":[113],"prediction.":[114],"This":[115],"weakly":[116],"coupled":[117],"manner":[118],"modeling":[120],"overlooks":[121],"interactions":[124,158,185],"among":[125],"nodes,":[126],"which":[127],"introduces":[128],"early":[130],"summarization":[131],"issue.":[132],"In":[133],"this":[134,236],"paper,":[135],"we":[136,151,197],"propose":[137,163],"end-to-end":[139],"Neighborhood-based":[140],"Interaction":[141],"Model":[142],"for":[143],"Recommendation":[144],"(NIRec)":[145],"address":[147],"above":[148],"Specifically,":[150],"first":[152,239],"analyze":[153],"significance":[155],"learning":[157,192],"HINs":[160],"then":[162],"a":[164,201],"novel":[165],"formulation":[166],"capture":[168],"interactive":[170],"patterns":[171],"each":[173],"pair":[174],"nodes":[176],"through":[177],"their":[178],"metapath-guided":[179],"neighborhoods.":[180],"Then,":[181],"explore":[183],"metapaths":[187],"deal":[189],"complexity":[193],"large-scale":[195],"networks,":[196],"formulate":[198],"interaction":[199,245],"convolutional":[202],"way":[203],"efficiently":[206],"fast":[208],"Fourier":[209],"transform.":[210],"The":[211],"extensive":[212],"experiments":[213],"four":[215],"types":[217],"demonstrate":[221],"gains":[224],"NIRec":[226],"comparing":[227],"state-of-the-arts.":[229],"To":[230],"best":[232],"our":[234],"knowledge,":[235],"work":[240],"providing":[241],"efficient":[243],"neighborhood-based":[244],"model":[246],"recommendations.":[250]},"counts_by_year":[{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":28},{"year":2021,"cited_by_count":25},{"year":2020,"cited_by_count":5}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
