{"id":"https://openalex.org/W2911926823","doi":"https://doi.org/10.1145/3308558.3313700","title":"A Scalable Hybrid Research Paper Recommender System for Microsoft Academic","display_name":"A Scalable Hybrid Research Paper Recommender System for Microsoft Academic","publication_year":2019,"publication_date":"2019-05-13","ids":{"openalex":"https://openalex.org/W2911926823","doi":"https://doi.org/10.1145/3308558.3313700","mag":"2911926823"},"language":"en","primary_location":{"id":"doi:10.1145/3308558.3313700","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3308558.3313700","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":"The World Wide Web Conference","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3308558.3313700","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015163336","display_name":"Anshul Kanakia","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anshul Kanakia","raw_affiliation_strings":["Microsoft, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056112689","display_name":"Z. Shen","orcid":"https://orcid.org/0000-0003-1391-5384"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhihong Shen","raw_affiliation_strings":["Microsoft, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085097872","display_name":"Darrin Eide","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Darrin Eide","raw_affiliation_strings":["Microsoft, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041659067","display_name":"Kuansan Wang","orcid":"https://orcid.org/0000-0001-7089-7966"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kuansan Wang","raw_affiliation_strings":["Microsoft, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":15.5174,"has_fulltext":false,"cited_by_count":71,"citation_normalized_percentile":{"value":0.98960218,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2893","last_page":"2899"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T10028","display_name":"Topic Modeling","score":0.9988999962806702,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9970999956130981,"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/recommender-system","display_name":"Recommender system","score":0.8961594104766846},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8340669870376587},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6654364466667175},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6018017530441284},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.5869089961051941},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.5316057205200195},{"id":"https://openalex.org/keywords/citation","display_name":"Citation","score":0.5198612809181213},{"id":"https://openalex.org/keywords/scripting-language","display_name":"Scripting language","score":0.5161412954330444},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.43804487586021423},{"id":"https://openalex.org/keywords/prioritization","display_name":"Prioritization","score":0.423421710729599},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.42239969968795776},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.25759708881378174},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.1510559320449829}],"concepts":[{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8961594104766846},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8340669870376587},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6654364466667175},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6018017530441284},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.5869089961051941},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.5316057205200195},{"id":"https://openalex.org/C2778805511","wikidata":"https://www.wikidata.org/wiki/Q1713","display_name":"Citation","level":2,"score":0.5198612809181213},{"id":"https://openalex.org/C61423126","wikidata":"https://www.wikidata.org/wiki/Q187432","display_name":"Scripting language","level":2,"score":0.5161412954330444},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.43804487586021423},{"id":"https://openalex.org/C2777615720","wikidata":"https://www.wikidata.org/wiki/Q11888847","display_name":"Prioritization","level":2,"score":0.423421710729599},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42239969968795776},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.25759708881378174},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.1510559320449829},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","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/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3308558.3313700","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3308558.3313700","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":"The World Wide Web Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1905.08880","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1905.08880","pdf_url":"https://arxiv.org/pdf/1905.08880","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":"doi:10.1145/3308558.3313700","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3308558.3313700","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":"The World Wide Web Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W281665770","https://openalex.org/W1015675232","https://openalex.org/W1493430969","https://openalex.org/W1790954942","https://openalex.org/W1813388215","https://openalex.org/W1932742904","https://openalex.org/W2005207065","https://openalex.org/W2023930240","https://openalex.org/W2024844926","https://openalex.org/W2084665596","https://openalex.org/W2124470082","https://openalex.org/W2131744502","https://openalex.org/W2141763599","https://openalex.org/W2142574815","https://openalex.org/W2150376021","https://openalex.org/W2153579005","https://openalex.org/W2294906672","https://openalex.org/W2493916176","https://openalex.org/W2604332200","https://openalex.org/W2610002097","https://openalex.org/W2787905871","https://openalex.org/W2793071066","https://openalex.org/W2805550038","https://openalex.org/W2811162191","https://openalex.org/W2883199673","https://openalex.org/W2950577311","https://openalex.org/W2952313649","https://openalex.org/W2963026768","https://openalex.org/W2963112422","https://openalex.org/W2963464979","https://openalex.org/W4255299494","https://openalex.org/W4294170691","https://openalex.org/W7052942652"],"related_works":["https://openalex.org/W2381242807","https://openalex.org/W3126131230","https://openalex.org/W2347541121","https://openalex.org/W2080951048","https://openalex.org/W4288804799","https://openalex.org/W3032237421","https://openalex.org/W2390346111","https://openalex.org/W3011883280","https://openalex.org/W2369082698","https://openalex.org/W2401808953"],"abstract_inverted_index":{"We":[0,49,104,135],"present":[1],"the":[2,7,40,51,106,124,127,147,174,187,198],"design":[3],"and":[4,29,57,74,85,122,132,146,177,186,206],"methodology":[5],"for":[6,22,68,83,167],"large":[8],"scale":[9],"hybrid":[10],"paper":[11,97,211],"recommender":[12,47,164],"system":[13,19,79,153,192],"used":[14],"by":[15,151,190],"Microsoft":[16,52],"Academic.":[17],"The":[18,171],"provides":[20],"recommendations":[21,108,188],"approximately":[23],"160":[24],"million":[25],"English":[26],"research":[27,61,205,210],"papers":[28,62],"patents.":[30],"Our":[31],"approach":[32,89],"handles":[33],"incomplete":[34],"citation":[35],"information":[36],"while":[37],"also":[38,81],"alleviating":[39],"cold-start":[41],"problem":[42],"that":[43,137,155],"often":[44],"affects":[45],"other":[46],"systems.":[48],"use":[50],"Academic":[53],"Graph":[54],"(MAG),":[55],"titles,":[56],"available":[58,183,194],"abstracts":[59],"of":[60,87,113,126,173,197],"to":[63,95,159,202],"build":[64],"a":[65,110,140],"recommendation":[66,102,119,212],"list":[67],"all":[69],"documents,":[70],"thereby":[71],"combining":[72],"co-citation":[73],"content":[75,168],"based":[76,169],"approaches.":[77],"Tuning":[78],"parameters":[80],"allows":[82,93],"blending":[84],"prioritization":[86],"each":[88],"which,":[90],"in":[91,101],"turn,":[92],"us":[94],"balance":[96],"novelty":[98],"versus":[99],"authority":[100],"results.":[103],"evaluate":[105],"generated":[107],"via":[109,184],"user":[111,175],"study":[112],"40":[114],"participants,":[115],"with":[116],"over":[117],"2400":[118],"pairs":[120],"graded":[121],"discuss":[123],"quality":[125],"results":[128,172],"using":[129],"[email":[130],"protected]":[131],"nDCG":[133],"scores.":[134],"see":[136],"there":[138],"is":[139],"strong":[141],"correlation":[142],"between":[143],"participant":[144],"scores":[145],"similarity":[148],"rankings":[149],"produced":[150,189],"our":[152,191],"but":[154],"additional":[156],"focus":[157],"needs":[158],"be":[160],"put":[161],"towards":[162],"improving":[163],"precision,":[165],"particularly":[166],"recommendations.":[170],"survey":[176],"associated":[178],"analysis":[179],"scripts":[180],"are":[181,193],"made":[182],"GitHub":[185],"as":[195],"part":[196],"MAG":[199],"on":[200],"Azure":[201],"facilitate":[203],"further":[204],"light":[207],"up":[208],"novel":[209],"applications.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2019-02-21T00:00:00"}