{"id":"https://openalex.org/W2035342005","doi":"https://doi.org/10.1145/2813448.2813511","title":"E-Commerce Item Recommendation Based on Field-aware Factorization Machine","display_name":"E-Commerce Item Recommendation Based on Field-aware Factorization Machine","publication_year":2015,"publication_date":"2015-09-15","ids":{"openalex":"https://openalex.org/W2035342005","doi":"https://doi.org/10.1145/2813448.2813511","mag":"2035342005"},"language":"en","primary_location":{"id":"doi:10.1145/2813448.2813511","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2813448.2813511","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 International ACM Recommender Systems Challenge","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/A5083660601","display_name":"Yan Peng","orcid":"https://orcid.org/0000-0001-5003-6923"},"institutions":[{"id":"https://openalex.org/I4210091137","display_name":"NetEase (China)","ror":"https://ror.org/00fp6fj05","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091137"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peng Yan","raw_affiliation_strings":["NetEase Youdao, Beijing, China"],"affiliations":[{"raw_affiliation_string":"NetEase Youdao, Beijing, China","institution_ids":["https://openalex.org/I4210091137"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023904026","display_name":"Xiaocong Zhou","orcid":"https://orcid.org/0000-0003-3756-3483"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaocong Zhou","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108663480","display_name":"Yitao Duan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091137","display_name":"NetEase (China)","ror":"https://ror.org/00fp6fj05","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091137"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yitao Duan","raw_affiliation_strings":["NetEase Youdao, Beijing, China"],"affiliations":[{"raw_affiliation_string":"NetEase Youdao, Beijing, China","institution_ids":["https://openalex.org/I4210091137"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5083660601"],"corresponding_institution_ids":["https://openalex.org/I4210091137"],"apc_list":null,"apc_paid":null,"fwci":7.1514,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.96810842,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T11478","display_name":"Caching and Content Delivery","score":0.984499990940094,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.978600025177002,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7122769355773926},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6656589508056641},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.618617057800293},{"id":"https://openalex.org/keywords/contest","display_name":"CONTEST","score":0.6032874584197998},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5768699645996094},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.5740275382995605},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.553674042224884},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5525029301643372},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5280207991600037},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.5100207924842834},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4613592326641083},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.45058271288871765},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4319433569908142},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4147830903530121},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3080904483795166},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22358906269073486},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1553802192211151},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.08686459064483643}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7122769355773926},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6656589508056641},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.618617057800293},{"id":"https://openalex.org/C2777582232","wikidata":"https://www.wikidata.org/wiki/Q5013414","display_name":"CONTEST","level":2,"score":0.6032874584197998},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5768699645996094},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.5740275382995605},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.553674042224884},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5525029301643372},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5280207991600037},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.5100207924842834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4613592326641083},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.45058271288871765},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4319433569908142},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4147830903530121},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3080904483795166},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22358906269073486},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1553802192211151},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.08686459064483643},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2813448.2813511","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2813448.2813511","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 International ACM Recommender Systems Challenge","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.49000000953674316}],"awards":[],"funders":[{"id":"https://openalex.org/F4320323900","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1678356000","https://openalex.org/W2017121215","https://openalex.org/W2076618162","https://openalex.org/W2094286023","https://openalex.org/W2295739661"],"related_works":["https://openalex.org/W2946214509","https://openalex.org/W2606108738","https://openalex.org/W4286740636","https://openalex.org/W2628063975","https://openalex.org/W2356479129","https://openalex.org/W2387346515","https://openalex.org/W2352196451","https://openalex.org/W2590086693","https://openalex.org/W2381260192","https://openalex.org/W3172679575"],"abstract_inverted_index":{"The":[0],"RecSys":[1],"2015":[2],"contest":[3],"[1]":[4],"seeks":[5],"the":[6,19,29,33,39,45,59,99,105,122,126],"best":[7],"solution":[8,36,97,114],"to":[9,24,109],"a":[10,50,92,116],"top-N":[11,46],"e-commerce":[12],"item":[13],"recommendation":[14,47],"problem.":[15],"This":[16,96],"paper":[17],"describes":[18],"team":[20],"Random":[21],"Walker's":[22],"approach":[23],"this":[25],"challenge,":[26],"which":[27],"won":[28],"3rd":[30],"place":[31,124],"in":[32,121],"contest.":[34],"Our":[35,112],"consists":[37],"of":[38,101,118],"following":[40],"components.":[41],"Firstly,":[42],"we":[43,63,79],"cast":[44],"task":[48],"into":[49],"binary":[51],"classification":[52],"problem":[53],"and":[54,72,88,104],"extract":[55],"original":[56],"features":[57,66],"from":[58],"raw":[60],"data.":[61],"Secondly,":[62],"learn":[64],"derived":[65],"using":[67],"field-aware":[68],"factorization":[69],"machines":[70],"(FFM)":[71],"gradient":[73],"boosting":[74],"decision":[75],"tree":[76],"(GBDT).":[77],"Lastly,":[78],"train":[80],"2":[81],"FFM":[82],"models":[83],"with":[84],"different":[85],"feature":[86],"sets":[87],"combine":[89],"them":[90],"by":[91],"non-linear":[93],"weighted":[94],"blending.":[95],"is":[98],"result":[100],"numerous":[102],"tests":[103],"scheme":[106],"turns":[107],"out":[108],"be":[110],"effective.":[111],"final":[113],"achieved":[115],"score":[117],"61075.2,":[119],"ranking":[120],"third":[123],"on":[125],"public":[127],"leaderboard.":[128]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
