{"id":"https://openalex.org/W1994389483","doi":"https://doi.org/10.1145/1401890.1401944","title":"Factorization meets the neighborhood","display_name":"Factorization meets the neighborhood","publication_year":2008,"publication_date":"2008-08-24","ids":{"openalex":"https://openalex.org/W1994389483","doi":"https://doi.org/10.1145/1401890.1401944","mag":"1994389483"},"language":"en","primary_location":{"id":"doi:10.1145/1401890.1401944","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1401890.1401944","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and 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/A5113974966","display_name":"Yehuda Koren","orcid":null},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yehuda Koren","raw_affiliation_strings":["AT&T, Florham Park, NJ, USA","At&t, Florham Park, NJ, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AT&T, Florham Park, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"At&t, Florham Park, NJ, USA#TAB#","institution_ids":["https://openalex.org/I1283103587"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5113974966"],"corresponding_institution_ids":["https://openalex.org/I1283103587"],"apc_list":null,"apc_paid":null,"fwci":180.2876,"has_fulltext":false,"cited_by_count":3926,"citation_normalized_percentile":{"value":0.99986513,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"426","last_page":"434"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":1.0,"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":1.0,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8619516491889954},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.7873777151107788},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7472394704818726},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.7060701251029968},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.6925123929977417},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.6586964726448059},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6048858761787415},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.48368439078330994},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43722620606422424},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.41917213797569275},{"id":"https://openalex.org/keywords/factor-analysis","display_name":"Factor analysis","score":0.41674357652664185},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38072097301483154},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35581690073013306},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.0750918984413147},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.0653424859046936}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8619516491889954},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7873777151107788},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7472394704818726},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7060701251029968},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.6925123929977417},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.6586964726448059},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6048858761787415},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.48368439078330994},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43722620606422424},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.41917213797569275},{"id":"https://openalex.org/C10879293","wikidata":"https://www.wikidata.org/wiki/Q726474","display_name":"Factor analysis","level":2,"score":0.41674357652664185},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38072097301483154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35581690073013306},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0750918984413147},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0653424859046936},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1401890.1401944","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1401890.1401944","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W40442397","https://openalex.org/W1652319903","https://openalex.org/W1832221731","https://openalex.org/W1880262756","https://openalex.org/W1966553486","https://openalex.org/W1992270714","https://openalex.org/W2018573356","https://openalex.org/W2037594831","https://openalex.org/W2042281163","https://openalex.org/W2049455633","https://openalex.org/W2056760161","https://openalex.org/W2061212083","https://openalex.org/W2070786785","https://openalex.org/W2085937320","https://openalex.org/W2099866409","https://openalex.org/W2126159342","https://openalex.org/W2134584261","https://openalex.org/W2137245235","https://openalex.org/W2147152072","https://openalex.org/W2159094788","https://openalex.org/W2171960770","https://openalex.org/W2172249709","https://openalex.org/W2341535507","https://openalex.org/W4232980324","https://openalex.org/W6636888537","https://openalex.org/W7070499600"],"related_works":["https://openalex.org/W2772628444","https://openalex.org/W2735929803","https://openalex.org/W4220714703","https://openalex.org/W1484355083","https://openalex.org/W3008845055","https://openalex.org/W2098758514","https://openalex.org/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W2508671622","https://openalex.org/W2556532874"],"abstract_inverted_index":{"Recommender":[0],"systems":[1,12],"provide":[2],"users":[3,30,48],"with":[4],"personalized":[5],"suggestions":[6],"for":[7],"products":[8,58],"or":[9,59],"services.":[10],"These":[11],"often":[13],"rely":[14],"on":[15,111,122,140],"Collaborating":[16],"Filtering":[17],"(CF),":[18],"where":[19],"past":[20],"transactions":[21],"are":[22,40,91,109,116],"analyzed":[23],"in":[24],"order":[25],"to":[26,38,68,97],"establish":[27],"connections":[28],"between":[29,57],"and":[31,49,51,73,101],"products.":[32],"The":[33,71,107],"two":[34],"more":[35,84],"successful":[36],"approaches":[37],"CF":[39],"latent":[41],"factor":[42,72],"models,":[43,53],"which":[44,54,133],"directly":[45],"profile":[46],"both":[47,69,99],"products,":[50],"neighborhood":[52,74],"analyze":[55],"similarities":[56],"users.":[60,106],"In":[61,125],"this":[62],"work":[63],"we":[64,127],"introduce":[65],"some":[66],"innovations":[67],"approaches.":[70],"models":[75,96],"can":[76],"now":[77],"be":[78],"smoothly":[79],"merged,":[80],"thereby":[81],"building":[82],"a":[83,129,144],"accurate":[85],"combined":[86],"model.":[87],"Further":[88],"accuracy":[89],"improvements":[90],"achieved":[92],"by":[93,104],"extending":[94],"the":[95,105,112,135],"exploit":[98],"explicit":[100],"implicit":[102],"feedback":[103],"methods":[108],"tested":[110],"Netflix":[113],"data.":[114],"Results":[115],"better":[117],"than":[118],"those":[119],"previously":[120],"published":[121],"that":[123],"dataset.":[124],"addition,":[126],"suggest":[128],"new":[130],"evaluation":[131],"metric,":[132],"highlights":[134],"differences":[136],"among":[137],"methods,":[138],"based":[139],"their":[141],"performance":[142],"at":[143],"top-K":[145],"recommendation":[146],"task.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":27},{"year":2025,"cited_by_count":125},{"year":2024,"cited_by_count":212},{"year":2023,"cited_by_count":230},{"year":2022,"cited_by_count":292},{"year":2021,"cited_by_count":393},{"year":2020,"cited_by_count":371},{"year":2019,"cited_by_count":387},{"year":2018,"cited_by_count":304},{"year":2017,"cited_by_count":316},{"year":2016,"cited_by_count":250},{"year":2015,"cited_by_count":230},{"year":2014,"cited_by_count":250},{"year":2013,"cited_by_count":185},{"year":2012,"cited_by_count":147}],"updated_date":"2026-05-09T13:55:54.758798","created_date":"2025-10-10T00:00:00"}