{"id":"https://openalex.org/W2626873216","doi":"https://doi.org/10.1145/3055635.3056633","title":"Grid-based Gaussian Processes Factorization Machine for Recommender Systems","display_name":"Grid-based Gaussian Processes Factorization Machine for Recommender Systems","publication_year":2017,"publication_date":"2017-02-24","ids":{"openalex":"https://openalex.org/W2626873216","doi":"https://doi.org/10.1145/3055635.3056633","mag":"2626873216"},"language":"en","primary_location":{"id":"doi:10.1145/3055635.3056633","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3055635.3056633","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Machine Learning and Computing","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/A5101557795","display_name":"Xu Huang","orcid":"https://orcid.org/0000-0002-8032-8270"},"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"]},{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xu Huang","raw_affiliation_strings":["Shenzhen Key Laboratory of Broad-band Network &amp; Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Broad-band Network &amp; Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020953714","display_name":"Yujiu Yang","orcid":"https://orcid.org/0000-0002-6427-1024"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"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":"Yujiu Yang","raw_affiliation_strings":["Shenzhen Key Laboratory of Broad-band Network &amp; Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Broad-band Network &amp; Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085691550","display_name":"Xianyu Bao","orcid":"https://orcid.org/0000-0003-1590-083X"},"institutions":[{"id":"https://openalex.org/I4210097984","display_name":"Shenzhen Academy of Inspection and Quarantine","ror":"https://ror.org/011v81t74","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210097984"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianyu Bao","raw_affiliation_strings":["Shenzhen Academy of Inspection and Quarantine, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Academy of Inspection and Quarantine, Shenzhen, China","institution_ids":["https://openalex.org/I4210097984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101557795"],"corresponding_institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06623322,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"92","last_page":"97"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9983000159263611,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9961000084877014,"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":0.9857000112533569,"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/recommender-system","display_name":"Recommender system","score":0.8373945951461792},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8042770028114319},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.6556103825569153},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.6529896855354309},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.6342893838882446},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5342501997947693},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5096108913421631},{"id":"https://openalex.org/keywords/lexicographical-order","display_name":"Lexicographical order","score":0.5001969337463379},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4897646903991699},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.47171634435653687},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.47078531980514526},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46686410903930664},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4573260545730591},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3804534375667572},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3455580472946167},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32558274269104004},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1240229606628418}],"concepts":[{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8373945951461792},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8042770028114319},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.6556103825569153},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.6529896855354309},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.6342893838882446},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5342501997947693},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5096108913421631},{"id":"https://openalex.org/C159254197","wikidata":"https://www.wikidata.org/wiki/Q1144915","display_name":"Lexicographical order","level":2,"score":0.5001969337463379},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4897646903991699},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.47171634435653687},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.47078531980514526},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46686410903930664},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4573260545730591},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3804534375667572},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3455580472946167},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32558274269104004},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1240229606628418},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3055635.3056633","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3055635.3056633","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Machine Learning and Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W937687500","https://openalex.org/W1746819321","https://openalex.org/W1770617812","https://openalex.org/W1973616272","https://openalex.org/W1994389483","https://openalex.org/W2112545207","https://openalex.org/W2137245235","https://openalex.org/W2148007822","https://openalex.org/W2170551306","https://openalex.org/W2295739661"],"related_works":["https://openalex.org/W3109911900","https://openalex.org/W4312998587","https://openalex.org/W1575318294","https://openalex.org/W3080740766","https://openalex.org/W3166581859","https://openalex.org/W2909865466","https://openalex.org/W2032039661","https://openalex.org/W4386143129","https://openalex.org/W2908124738","https://openalex.org/W2000026009"],"abstract_inverted_index":{"Matrix":[0,20,65],"Factorization":[1,21,66,82,157],"(MF)":[2],"is":[3,37,51,86,171],"an":[4],"effective":[5],"approach":[6,147],"to":[7,92,115,136],"Collaborative":[8],"Filtering":[9],"(CF)":[10],"in":[11,40,134,166],"the":[12,18,26,54,63,94,116,128,138,149,152,161,169],"field":[13],"of":[14,29,48,58,118,151],"recommender":[15],"systems.":[16],"However,":[17],"traditional":[19,64,162],"method":[22,67,154,164],"can":[23],"only":[24,45],"model":[25,77],"linear":[27],"interaction":[28],"latent":[30,129],"features":[31,130],"between":[32,97],"users":[33,60,98,175],"and":[34,53,99,104,160,173],"items,":[35],"which":[36,85],"not":[38],"convincing":[39],"reality.":[41],"In":[42,70],"addition,":[43],"when":[44],"sparse":[46,172],"dataset":[47],"small":[49],"size":[50,117],"available":[52],"historic":[55],"behavior":[56],"logs":[57],"most":[59,174],"are":[61,176],"scarce,":[62],"behaves":[68],"badly.":[69],"this":[71],"paper,":[72],"we":[73,126,142],"propose":[74],"a":[75],"new":[76],"called":[78],"Grid-based":[79],"Gaussian":[80,89,155],"Processes":[81,90,156],"Machine":[83,158],"(GGPFM),":[84],"based":[87],"on":[88],"(GP),":[91],"capture":[93],"nonlinear":[95],"relationship":[96],"items.":[100],"The":[101],"generic":[102],"inference":[103],"learning":[105],"algorithms":[106],"for":[107],"GP":[108,124],"regression":[109],"have":[110],"cubic":[111],"complexity":[112],"with":[113,131],"respect":[114],"dataset.":[119],"Rather":[120],"than":[121],"using":[122],"off-the-shelf":[123],"model,":[125],"endow":[127],"grid":[132],"structures":[133],"order":[135],"decrease":[137],"model's":[139],"complexity.":[140],"Finally,":[141],"empirically":[143],"show":[144],"that":[145],"our":[146],"outperforms":[148],"state":[150],"art":[153],"(GPFM)":[159],"MF":[163],"significantly":[165],"cases":[167],"where":[168],"data":[170],"inactive.":[177]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
