{"id":"https://openalex.org/W7096409082","doi":null,"title":"Hidden Factors and Hidden Topics: Understanding Rating Dimensions with Review Text. Extended version http://i.stanford.edu/~julian/pdfs/ recsys_extended.pdf","display_name":"Hidden Factors and Hidden Topics: Understanding Rating Dimensions with Review Text. Extended version http://i.stanford.edu/~julian/pdfs/ recsys_extended.pdf","publication_year":2015,"publication_date":"2015-10-19","ids":{"openalex":"https://openalex.org/W7096409082"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.648.4455","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.648.4455","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cseweb.ucsd.edu/~jmcauley/pdfs/recsys13.pdf","raw_type":"text"},"volume":null,"type":"article","indexed_in":[],"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/A5021827617","display_name":"Julian McAuley","orcid":"https://orcid.org/0000-0003-0955-7588","observed_orcids":["https://orcid.org/0000-0003-0955-7588"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Julian Mcauley","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5091272738","display_name":"Jure Leskovec","orcid":"https://orcid.org/0000-0002-5411-923X","observed_orcids":["https://orcid.org/0000-0002-5411-923X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jure Leskovec","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.71174049,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9951000213623047,"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":0.9951000213623047,"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":0.0008999999845400453,"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":0.0006000000284984708,"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/review-text","display_name":"review text","score":0.7350000143051147},{"id":"https://openalex.org/keywords/latent-topic-models","display_name":"latent topic models","score":0.5820000171661377},{"id":"https://openalex.org/keywords/latent-factor-models","display_name":"latent factor models","score":0.5379999876022339},{"id":"https://openalex.org/keywords/recommender-systems","display_name":"recommender systems","score":0.7509999871253967},{"id":"https://openalex.org/keywords/rating-prediction","display_name":"rating prediction","score":0.7950000166893005},{"id":"https://openalex.org/keywords/user-preferences","display_name":"user preferences","score":0.37299999594688416},{"id":"https://openalex.org/keywords/product-attributes","display_name":"product attributes","score":0.5740000009536743}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7164000272750854},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5712000131607056},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5263000130653381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4715999960899353},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.46810001134872437},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.4406999945640564},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.40639999508857727},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.39559999108314514},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.3865000009536743},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3797999918460846},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3783999979496002},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.37770000100135803},{"id":"https://openalex.org/C65965080","wikidata":"https://www.wikidata.org/wiki/Q1806885","display_name":"Latent variable model","level":3,"score":0.352400004863739},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3359000086784363},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.3131999969482422},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.2987000048160553},{"id":"https://openalex.org/C147101817","wikidata":"https://www.wikidata.org/wiki/Q13443840","display_name":"Product category","level":3,"score":0.2858999967575073},{"id":"https://openalex.org/C112933361","wikidata":"https://www.wikidata.org/wiki/Q2845258","display_name":"Probabilistic latent semantic analysis","level":2,"score":0.26489999890327454}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.648.4455","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.648.4455","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cseweb.ucsd.edu/~jmcauley/pdfs/recsys13.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.649.9048","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.649.9048","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cs.stanford.edu/people/jure/pubs/reviews-recsys13.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7099323099","https://openalex.org/W2061873838","https://openalex.org/W2983883274","https://openalex.org/W2513402967","https://openalex.org/W2290642084","https://openalex.org/W3159215852","https://openalex.org/W2296540299","https://openalex.org/W2573167395","https://openalex.org/W2741609276","https://openalex.org/W3088724481"],"abstract_inverted_index":{"In":[0,128],"order":[1,43],"to":[2,5,16,44,55,77,115,133,177,214,240,250],"recommend":[3],"products":[4,205],"users":[6],"we":[7,23,131,164],"must":[8,24],"ultimately":[9],"pre-dict":[10],"how":[11],"a":[12,17,47,93,125,230],"user":[13,31,48,83,109],"will":[14,49],"respond":[15],"new":[18,204],"product.":[19,39],"To":[20],"do":[21],"so":[22],"uncover":[25],"the":[26,35,58,66,90,120,193,226],"implicit":[27],"tastes":[28],"of":[29,37,69,92,141,228],"each":[30,38],"as":[32,34,63,65,139,150,245],"well":[33,64],"properties":[36],"For":[40],"example,":[41],"in":[42,71,89,196],"predict":[45],"whether":[46],"enjoy":[50],"Harry":[51],"Potter,":[52],"it":[53],"helps":[54,175],"identify":[56,251],"that":[57,123],"book":[59],"is":[60,75,200],"about":[61],"wiz-ards,":[62],"user\u2019s":[67,126],"level":[68],"interest":[70],"wizardry.":[72],"User":[73],"feed-back":[74],"required":[76],"discover":[78],"these":[79],"latent":[80,112,135,146,171,217],"product":[81,111,189],"and":[82,110,206,249,253],"dimen-sions.":[84],"Such":[85],"feedback":[86],"often":[87,103],"comes":[88],"form":[91],"numeric":[94],"rating":[95,136,172],"accompanied":[96],"by":[97,153,191],"review":[98,105,147,197],"text.":[99,182],"However,":[100],"traditional":[101],"methods":[102],"discard":[104],"text,":[106],"which":[107,174],"makes":[108],"dimen-sions":[113],"difficult":[114],"interpret,":[116],"since":[117],"they":[118],"ignore":[119],"very":[121],"text":[122,227],"justi-fies":[124],"rating.":[127],"this":[129,199],"paper,":[130],"aim":[132],"combine":[134],"dimensions":[137],"(such":[138,149],"those":[140,151],"latent-factor":[142],"recommender":[143],"systems)":[144],"with":[145,181],"topics":[148,236],"learned":[152],"topic":[154],"models":[155],"like":[156],"LDA).":[157],"Our":[158],"approach":[159,185],"has":[160],"several":[161],"advantages.":[162],"Firstly,":[163],"ob-tain":[165],"highly":[166],"interpretable":[167],"textual":[168],"labels":[169],"for":[170,203],"dimensions,":[173],"us":[176],"\u2018justify":[178],"\u2019":[179],"ratings":[180,190,213],"Secondly,":[183],"our":[184,234],"more":[186],"accurately":[187],"predicts":[188],"harnessing":[192],"informa-tion":[194],"present":[195],"text;":[198],"especially":[201],"true":[202],"users,":[207],"who":[208],"may":[209,220],"have":[210],"too":[211],"few":[212],"model":[215],"their":[216],"fac-tors,":[218],"yet":[219],"still":[221],"provide":[222],"substantial":[223],"information":[224],"from":[225],"even":[229],"single":[231],"review.":[232],"Thirdly,":[233],"discovered":[235],"can":[237],"be":[238],"used":[239],"facilitate":[241],"other":[242],"tasks":[243],"such":[244],"automated":[246],"genre":[247],"discovery,":[248],"useful":[252],"representative":[254],"reviews.":[255]},"counts_by_year":[],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2025-10-27T00:00:00"}