{"id":"https://openalex.org/W2513487204","doi":"https://doi.org/10.1145/2959100.2959107","title":"Generating Pseudotransactions for Improving Sparse Matrix Factorization","display_name":"Generating Pseudotransactions for Improving Sparse Matrix Factorization","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2513487204","doi":"https://doi.org/10.1145/2959100.2959107","mag":"2513487204"},"language":"en","primary_location":{"id":"doi:10.1145/2959100.2959107","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2959100.2959107","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM Conference on Recommender Systems","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/A5101584726","display_name":"Agung Wibowo","orcid":"https://orcid.org/0000-0002-5278-1684"},"institutions":[{"id":"https://openalex.org/I195460627","display_name":"University of Aberdeen","ror":"https://ror.org/016476m91","country_code":"GB","type":"education","lineage":["https://openalex.org/I195460627"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Agung Toto Wibowo","raw_affiliation_strings":["University of Aberdeen, Aberdeen, Scotland Uk"],"affiliations":[{"raw_affiliation_string":"University of Aberdeen, Aberdeen, Scotland Uk","institution_ids":["https://openalex.org/I195460627"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101584726"],"corresponding_institution_ids":["https://openalex.org/I195460627"],"apc_list":null,"apc_paid":null,"fwci":1.327,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.86282351,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"439","last_page":"442"},"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9782000184059143,"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/T12384","display_name":"Customer churn and segmentation","score":0.9739000201225281,"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/movielens","display_name":"MovieLens","score":0.8846817016601562},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.7253841161727905},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.7132254838943481},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.6804198622703552},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.6317365169525146},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.59651118516922},{"id":"https://openalex.org/keywords/incomplete-lu-factorization","display_name":"Incomplete LU factorization","score":0.5789741277694702},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5683914422988892},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.5072588324546814},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4770973324775696},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43980562686920166},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33916276693344116},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1524609625339508}],"concepts":[{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.8846817016601562},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.7253841161727905},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.7132254838943481},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.6804198622703552},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.6317365169525146},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.59651118516922},{"id":"https://openalex.org/C134978465","wikidata":"https://www.wikidata.org/wiki/Q1654069","display_name":"Incomplete LU factorization","level":4,"score":0.5789741277694702},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5683914422988892},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.5072588324546814},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4770973324775696},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43980562686920166},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33916276693344116},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1524609625339508},{"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2959100.2959107","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2959100.2959107","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM Conference on Recommender Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W40442397","https://openalex.org/W72893484","https://openalex.org/W237298919","https://openalex.org/W281665770","https://openalex.org/W1902027874","https://openalex.org/W1990630329","https://openalex.org/W2009415795","https://openalex.org/W2017288758","https://openalex.org/W2018571751","https://openalex.org/W2025605741","https://openalex.org/W2041022395","https://openalex.org/W2061460268","https://openalex.org/W2076566842","https://openalex.org/W2100235918","https://openalex.org/W2116206254","https://openalex.org/W2121710227","https://openalex.org/W2129211739","https://openalex.org/W2135029798","https://openalex.org/W2219888463","https://openalex.org/W2334658737","https://openalex.org/W2963363076","https://openalex.org/W3143596294","https://openalex.org/W4244404635"],"related_works":["https://openalex.org/W2355698112","https://openalex.org/W2022984797","https://openalex.org/W4394818607","https://openalex.org/W2986679525","https://openalex.org/W2797500822","https://openalex.org/W2794458286","https://openalex.org/W4205822456","https://openalex.org/W4299358966","https://openalex.org/W2537367858","https://openalex.org/W3173811578"],"abstract_inverted_index":{"Recent":[0],"research":[1],"on":[2,10,136],"Recommender":[3],"Systems,":[4],"specifically":[5],"Collaborative":[6],"Filtering,":[7],"has":[8],"focussed":[9],"Matrix":[11,36],"Factorization":[12],"(MF)":[13],"methods,":[14],"which":[15],"have":[16],"been":[17],"shown":[18],"to":[19,23,88,98,102,116],"provide":[20],"good":[21],"solutions":[22],"the":[24,30,40,43,80,83,99,107,118,122,137],"cold":[25],"start":[26],"problem.":[27],"However,":[28],"typically":[29],"same":[31],"settings":[32],"are":[33,96],"used":[34],"for":[35,51,58,64,141],"factorization":[37],"regardless":[38],"of":[39,42,93,139],"density":[41],"matrix.":[44],"In":[45],"our":[46],"experiments,":[47],"we":[48],"found":[49],"that":[50,95,131],"MF,":[52],"Root":[53],"Mean":[54],"Square":[55],"Error":[56],"(RMSE)":[57],"recommendations":[59],"increases":[60],"(i.e.":[61],"performance":[62,138],"drops)":[63],"sparse":[65,142],"matrices.":[66],"We":[67,125],"propose":[68],"a":[69,90],"Two":[70],"Stage":[71],"MF":[72,75,87,111,140],"approach":[73],"so":[74],"is":[76],"run":[77],"twice":[78],"over":[79,112],"whole":[81],"matrix;":[82],"first":[84],"stage":[85,109],"uses":[86],"generate":[89],"small":[91],"percentage":[92],"pseudotransactions":[94],"added":[97],"original":[100],"matrix":[101,115],"increase":[103],"its":[104],"density,":[105],"and":[106],"second":[108],"re-runs":[110],"this":[113],"denser":[114],"predict":[117],"user-item":[119],"transactions":[120],"in":[121],"testing":[123],"set.":[124],"show":[126],"using":[127],"data":[128],"from":[129],"Movielens":[130],"such":[132],"methods":[133],"can":[134],"improve":[135],"martrices.":[143]},"counts_by_year":[{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}