{"id":"https://openalex.org/W2595080281","doi":"https://doi.org/10.1145/3003728","title":"Recommendations Based on Comprehensively Exploiting the Latent Factors Hidden in Items\u2019 Ratings and Content","display_name":"Recommendations Based on Comprehensively Exploiting the Latent Factors Hidden in Items\u2019 Ratings and Content","publication_year":2017,"publication_date":"2017-03-10","ids":{"openalex":"https://openalex.org/W2595080281","doi":"https://doi.org/10.1145/3003728","mag":"2595080281"},"language":"en","primary_location":{"id":"doi:10.1145/3003728","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3003728","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-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/A5086115549","display_name":"Shanshan Feng","orcid":"https://orcid.org/0000-0002-6161-9232"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanshan Feng","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100648774","display_name":"Jian Cao","orcid":"https://orcid.org/0000-0002-0036-9436"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Cao","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101422661","display_name":"Jie Wang","orcid":"https://orcid.org/0000-0003-1857-5569"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jie Wang","raw_affiliation_strings":["Stanford University, Standford, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University, Standford, CA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041333646","display_name":"Shiyou Qian","orcid":"https://orcid.org/0000-0001-7775-1740"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiyou Qian","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.4721,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.9355261,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"11","issue":"3","first_page":"1","last_page":"27"},"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/T10028","display_name":"Topic Modeling","score":0.9868000149726868,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9800000190734863,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.772081732749939},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6539636254310608},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.5866999626159668},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.49343934655189514},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4856525659561157},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.4760465621948242},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.45859140157699585},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.4558800458908081},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.44775786995887756},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4468362629413605},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4455123543739319},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3859332203865051},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09631869196891785},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08688271045684814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.772081732749939},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6539636254310608},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.5866999626159668},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.49343934655189514},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4856525659561157},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.4760465621948242},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.45859140157699585},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4558800458908081},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.44775786995887756},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4468362629413605},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4455123543739319},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3859332203865051},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09631869196891785},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08688271045684814},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3003728","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3003728","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W39762900","https://openalex.org/W46938732","https://openalex.org/W91251986","https://openalex.org/W96181372","https://openalex.org/W178169250","https://openalex.org/W281665770","https://openalex.org/W331119053","https://openalex.org/W648165475","https://openalex.org/W1479822238","https://openalex.org/W1510348757","https://openalex.org/W1514107797","https://openalex.org/W1587694292","https://openalex.org/W1854214752","https://openalex.org/W1880262756","https://openalex.org/W1896115748","https://openalex.org/W1966553486","https://openalex.org/W1976618413","https://openalex.org/W1978044639","https://openalex.org/W1989534515","https://openalex.org/W1994389483","https://openalex.org/W1997219719","https://openalex.org/W2001082470","https://openalex.org/W2014371865","https://openalex.org/W2020678400","https://openalex.org/W2023185061","https://openalex.org/W2039118116","https://openalex.org/W2049455633","https://openalex.org/W2054141820","https://openalex.org/W2054553473","https://openalex.org/W2061212083","https://openalex.org/W2061873838","https://openalex.org/W2063049279","https://openalex.org/W2069078812","https://openalex.org/W2070786785","https://openalex.org/W2079335968","https://openalex.org/W2080512030","https://openalex.org/W2100235918","https://openalex.org/W2108153239","https://openalex.org/W2109992782","https://openalex.org/W2110325612","https://openalex.org/W2113273124","https://openalex.org/W2113858518","https://openalex.org/W2117311203","https://openalex.org/W2117354486","https://openalex.org/W2117420919","https://openalex.org/W2124029832","https://openalex.org/W2126700264","https://openalex.org/W2127300005","https://openalex.org/W2127480961","https://openalex.org/W2132708887","https://openalex.org/W2135505871","https://openalex.org/W2135790056","https://openalex.org/W2137245235","https://openalex.org/W2142144955","https://openalex.org/W2148044308","https://openalex.org/W2152828463","https://openalex.org/W2156338064","https://openalex.org/W2160555926","https://openalex.org/W2165395308","https://openalex.org/W2170304975","https://openalex.org/W2170512680","https://openalex.org/W2171960770","https://openalex.org/W2241862190","https://openalex.org/W3133677217","https://openalex.org/W4213357379"],"related_works":["https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W4246980185","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405","https://openalex.org/W4238861846","https://openalex.org/W3125580266","https://openalex.org/W44246808","https://openalex.org/W3160516639"],"abstract_inverted_index":{"To":[0],"improve":[1,64,262],"the":[2,48,65,68,113,183,196,235,256,263,296,320,323,361,367],"performance":[3,66,264],"of":[4,27,47,67,118,153,185,237,265,298,322,369],"recommender":[5,69,266],"systems":[6],"in":[7,157,220,232,247,252,353],"a":[8,99,170,273,305],"practical":[9],"manner,":[10],"several":[11],"hybrid":[12,29],"approaches":[13,30,75],"have":[14],"been":[15],"developed":[16],"by":[17,102,211,287,311],"considering":[18,44],"item":[19,292],"ratings":[20,50,143,160,249,290],"and":[21,51,53,82,150,159,191,216,250,260,282,291,329,340],"content":[22,251,293],"information":[23],"simultaneously.":[24],"However,":[25],"most":[26,117],"these":[28,74,119],"make":[31],"recommendations":[32],"based":[33,181],"on":[34,182,333],"aggregating":[35],"different":[36],"recommendation":[37,127,372],"techniques":[38],"using":[39],"various":[40],"strategies,":[41],"rather":[42,145],"than":[43,146],"joint":[45],"modeling":[46],"item\u2019s":[49],"content,":[52],"thus":[54,365],"fail":[55],"to":[56,77,90,97,125,203,207,222,226,241,254,261,318,360],"detect":[57],"many":[58],"latent":[59,105,136,154,177,188,244,284,314],"factors":[60,137,155,245],"that":[61,173,277,345,355],"could":[62],"potentially":[63,227],"systems.":[70,267],"For":[71],"this":[72,166,233,238,299],"reason,":[73],"continue":[76],"suffer":[78],"from":[79,107,138],"data":[80,257,362],"sparsity":[81,258,363],"do":[83],"not":[84,162],"work":[85,239],"well":[86,129],"for":[87,112,130,308,371],"recommending":[88],"items":[89,205,225,310],"individual":[91],"users.":[92,229],"A":[93],"few":[94],"studies":[95],"try":[96],"describe":[98],"user\u2019s":[100,306],"preference":[101,307],"detecting":[103,212],"items\u2019":[104,248,283],"features":[106,285],"content-description":[108],"texts":[109,158],"as":[110,176],"compensation":[111],"sparse":[114],"ratings.":[115],"Unfortunately,":[116],"methods":[120,332,351],"are":[121,161],"still":[122],"generally":[123],"unable":[124],"accomplish":[126],"tasks":[128],"two":[131],"reasons:":[132],"(1)":[133],"they":[134],"learn":[135],"text":[139],"descriptions":[140],"or":[141],"user--item":[142],"independently,":[144],"combining":[147],"them":[148],"together;":[149],"(2)":[151],"influences":[152],"hidden":[156,246],"fully":[163],"explored.":[164],"In":[165,316],"study,":[167],"we":[168,174,326],"propose":[169],"probabilistic":[171,275,300],"approach":[172,347],"denote":[175],"random":[178,192],"walk":[179,193],"(LRW)":[180],"combination":[184],"an":[186],"integrated":[187],"topic":[189,270],"model":[190,271],"(RW)":[194],"with":[195],"restart":[197],"method,":[198],"which":[199],"can":[200,303],"be":[201],"used":[202],"rank":[204],"according":[206],"expected":[208],"user":[209],"preferences":[210,281],"both":[213,289],"their":[214],"explicit":[215],"implicit":[217,280],"correlative":[218],"information,":[219],"order":[221,253,317],"recommend":[223],"top-ranked":[224],"interested":[228],"As":[230],"presented":[231],"article,":[234],"goal":[236],"is":[240,357],"comprehensively":[242],"discover":[243],"alleviate":[255],"problem":[259],"The":[268,342],"proposed":[269,324],"provides":[272],"generative":[274],"framework":[276],"discovers":[278],"users\u2019":[279],"simultaneously":[286],"exploiting":[288],"information.":[294],"On":[295],"basis":[297],"framework,":[301],"RW":[302],"predict":[304],"unrated":[309],"discovering":[312],"global":[313],"relations.":[315],"show":[319],"efficiency":[321],"approach,":[325],"test":[327],"LRW":[328,370],"other":[330],"state-of-the-art":[331],"three":[334],"real-world":[335],"datasets,":[336],"namely,":[337],"CAMRa2011,":[338],"Yahoo!,":[339],"APP.":[341],"experiments":[343],"indicate":[344],"our":[346],"outperforms":[348],"all":[349],"comparative":[350],"and,":[352],"addition,":[354],"it":[356],"less":[358],"sensitive":[359],"problem,":[364],"demonstrating":[366],"robustness":[368],"tasks.":[373]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
