{"id":"https://openalex.org/W2168228576","doi":"https://doi.org/10.1145/2162102.2162104","title":"Enhancing matrix factorization through initialization for implicit feedback databases","display_name":"Enhancing matrix factorization through initialization for implicit feedback databases","publication_year":2012,"publication_date":"2012-02-14","ids":{"openalex":"https://openalex.org/W2168228576","doi":"https://doi.org/10.1145/2162102.2162104","mag":"2168228576"},"language":"en","primary_location":{"id":"doi:10.1145/2162102.2162104","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2162102.2162104","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd Workshop on Context-awareness in Retrieval and Recommendation","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/A5012061499","display_name":"Bal\u00e1zs Hidasi","orcid":"https://orcid.org/0009-0004-4259-8781"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Bal\u00e1zs Hidasi","raw_affiliation_strings":["Budapest University of Technology and Economics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Budapest University of Technology and Economics","institution_ids":["https://openalex.org/I29770179"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070226189","display_name":"Domonkos Tikk","orcid":null},"institutions":[{"id":"https://openalex.org/I4210120779","display_name":"Fluid Gravity Engineering (United Kingdom)","ror":"https://ror.org/02cc4d683","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210120779"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Domonkos Tikk","raw_affiliation_strings":["Gravity R&amp;D Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gravity R&amp;D Ltd","institution_ids":["https://openalex.org/I4210120779"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4698,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.88468318,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2","last_page":"9"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9926000237464905,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9886999726295471,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.9268953800201416},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8193087577819824},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.6981540322303772},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.6967747807502747},{"id":"https://openalex.org/keywords/movielens","display_name":"MovieLens","score":0.66820228099823},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.6302465200424194},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6110544800758362},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5562437176704407},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.500340461730957},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.49233949184417725},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48384347558021545},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4803368151187897},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4350169599056244},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.41734153032302856},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.4131765365600586},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32271796464920044},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31799083948135376},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2464655041694641}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.9268953800201416},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8193087577819824},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.6981540322303772},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.6967747807502747},{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.66820228099823},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.6302465200424194},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6110544800758362},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5562437176704407},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.500340461730957},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.49233949184417725},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48384347558021545},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4803368151187897},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4350169599056244},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.41734153032302856},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4131765365600586},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32271796464920044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31799083948135376},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2464655041694641},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2162102.2162104","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2162102.2162104","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd Workshop on Context-awareness in Retrieval and Recommendation","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":25,"referenced_works":["https://openalex.org/W123693119","https://openalex.org/W1486317198","https://openalex.org/W1520995987","https://openalex.org/W1790954942","https://openalex.org/W1971040550","https://openalex.org/W1988139567","https://openalex.org/W1990846291","https://openalex.org/W1994389483","https://openalex.org/W2002519017","https://openalex.org/W2015583498","https://openalex.org/W2048426792","https://openalex.org/W2056760161","https://openalex.org/W2063468305","https://openalex.org/W2101409192","https://openalex.org/W2113802117","https://openalex.org/W2122538988","https://openalex.org/W2137245235","https://openalex.org/W2148694408","https://openalex.org/W2155106456","https://openalex.org/W2172249709","https://openalex.org/W2341535507","https://openalex.org/W2990138404","https://openalex.org/W2997904722","https://openalex.org/W4285719527","https://openalex.org/W4292023222"],"related_works":["https://openalex.org/W2797500822","https://openalex.org/W2355698112","https://openalex.org/W2022984797","https://openalex.org/W2986679525","https://openalex.org/W4205822456","https://openalex.org/W4299358966","https://openalex.org/W2537367858","https://openalex.org/W2981634480","https://openalex.org/W2188396403","https://openalex.org/W3173811578"],"abstract_inverted_index":{"The":[0,136],"implicit":[1,57,75,153,164],"feedback":[2,24,58],"based":[3,25,59,148],"recommendation":[4,26,44,80],"problem---when":[5],"only":[6,53],"the":[7,22,30,34,74,89,102,109,126,139,156],"user":[8,38],"history":[9],"is":[10,115,141,167],"available":[11],"but":[12],"there":[13,51],"are":[14,52],"no":[15],"ratings---is":[16],"a":[17,54,68,96],"much":[18],"harder":[19],"task":[20,45],"than":[21],"explicit":[23],"problem,":[27],"due":[28],"to":[29],"inherent":[31],"uncertainty":[32],"of":[33,36,88,138,155],"interpretation":[35],"such":[37],"feedbacks.":[39],"Still,":[40],"this":[41],"practically":[42],"important":[43],"received":[46],"less":[47],"attention":[48],"and":[49,61,77,146,160,179],"therefore":[50],"few":[55],"common":[56,69],"algorithms":[60],"benchmark":[62],"datasets.":[63],"This":[64],"paper":[65],"focuses":[66],"on":[67,151],"matrix":[70],"factorization":[71],"method":[72],"for":[73],"problem":[76],"investigates":[78],"if":[79],"performance":[81,170],"can":[82,130,172],"be":[83,131],"improved":[84],"by":[85],"appropriate":[86],"initialization":[87,98,128,140],"feature":[90,111],"vectors":[91],"before":[92],"training.":[93],"We":[94,123],"present":[95],"general":[97],"framework":[99,129],"that":[100,169],"preserves":[101],"similarity":[103,114,149],"between":[104],"entities":[105],"(users/items)":[106],"when":[107],"creating":[108],"initial":[110],"vectors,":[112],"where":[113],"defined":[116],"using":[117,143],"e.g.":[118],"context":[119,145],"or":[120],"metadata":[121,147],"information.":[122],"demonstrate":[124],"how":[125],"proposed":[127],"coupled":[132],"with":[133],"MF":[134],"algorithms.":[135],"efficiency":[137],"evaluated":[142],"various":[144],"concepts":[150],"two":[152],"variants":[154],"MovieLens":[157],"10M":[158],"dataset":[159],"one":[161],"real":[162],"life":[163],"database.":[165],"It":[166],"shown":[168],"gain":[171],"attain":[173],"10%":[174],"improvement":[175],"in":[176,180],"[email":[177,181],"protected]":[178,182]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
