{"id":"https://openalex.org/W3007876149","doi":"https://doi.org/10.1109/bigdata47090.2019.9006062","title":"Collaborative Ranking Tags and Items via Cross-domain Recommendation","display_name":"Collaborative Ranking Tags and Items via Cross-domain Recommendation","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3007876149","doi":"https://doi.org/10.1109/bigdata47090.2019.9006062","mag":"3007876149"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9006062","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006062","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","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/A5004341287","display_name":"Huiyuan Chen","orcid":"https://orcid.org/0000-0002-6360-558X"},"institutions":[{"id":"https://openalex.org/I58956616","display_name":"Case Western Reserve University","ror":"https://ror.org/051fd9666","country_code":"US","type":"education","lineage":["https://openalex.org/I58956616"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Huiyuan Chen","raw_affiliation_strings":["Department of Computer and Data Sciences, Case Western Reserve University"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Data Sciences, Case Western Reserve University","institution_ids":["https://openalex.org/I58956616"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100337051","display_name":"Jing Li","orcid":"https://orcid.org/0000-0003-1160-6959"},"institutions":[{"id":"https://openalex.org/I58956616","display_name":"Case Western Reserve University","ror":"https://ror.org/051fd9666","country_code":"US","type":"education","lineage":["https://openalex.org/I58956616"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jing Li","raw_affiliation_strings":["Department of Computer and Data Sciences, Case Western Reserve University"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Data Sciences, Case Western Reserve University","institution_ids":["https://openalex.org/I58956616"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5004341287"],"corresponding_institution_ids":["https://openalex.org/I58956616"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.30675573,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"721","last_page":"730"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T12303","display_name":"Tensor decomposition and applications","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9909999966621399,"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/computer-science","display_name":"Computer science","score":0.848619818687439},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.7184911966323853},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.7089386582374573},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6816768646240234},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6148157119750977},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5436491370201111},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5091955065727234},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.4938217103481293},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.4818626344203949},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.4451097548007965}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.848619818687439},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7184911966323853},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7089386582374573},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6816768646240234},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6148157119750977},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5436491370201111},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5091955065727234},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.4938217103481293},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.4818626344203949},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.4451097548007965},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9006062","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006062","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W331119053","https://openalex.org/W880911330","https://openalex.org/W1549014378","https://openalex.org/W1774304772","https://openalex.org/W1854214752","https://openalex.org/W1940008012","https://openalex.org/W1943444950","https://openalex.org/W1975153704","https://openalex.org/W1976801265","https://openalex.org/W2020791669","https://openalex.org/W2024165284","https://openalex.org/W2024356620","https://openalex.org/W2042281163","https://openalex.org/W2051093690","https://openalex.org/W2054141820","https://openalex.org/W2056088289","https://openalex.org/W2084527756","https://openalex.org/W2092694516","https://openalex.org/W2092803270","https://openalex.org/W2093953080","https://openalex.org/W2108753466","https://openalex.org/W2116429057","https://openalex.org/W2118674552","https://openalex.org/W2127201730","https://openalex.org/W2144487656","https://openalex.org/W2144807535","https://openalex.org/W2144920235","https://openalex.org/W2150449434","https://openalex.org/W2164278908","https://openalex.org/W2167143366","https://openalex.org/W2244405900","https://openalex.org/W2368841069","https://openalex.org/W2509893387","https://openalex.org/W2514885441","https://openalex.org/W2605327373","https://openalex.org/W2771079411","https://openalex.org/W2771332840","https://openalex.org/W2795104036","https://openalex.org/W2808745848","https://openalex.org/W2894087624","https://openalex.org/W2896239789","https://openalex.org/W2907272802","https://openalex.org/W2911419886","https://openalex.org/W2944008584","https://openalex.org/W2964053796","https://openalex.org/W2972965281","https://openalex.org/W3098758500","https://openalex.org/W4292363360","https://openalex.org/W6632758013","https://openalex.org/W6640485552","https://openalex.org/W6676253046","https://openalex.org/W6766170023"],"related_works":["https://openalex.org/W2772628444","https://openalex.org/W1484355083","https://openalex.org/W2735929803","https://openalex.org/W4220714703","https://openalex.org/W2098758514","https://openalex.org/W3008845055","https://openalex.org/W2170391450","https://openalex.org/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W2508671622"],"abstract_inverted_index":{"Tag":[0],"and":[1,85,98,148,160,168,181,196,217,245],"item":[2,167,197],"recommendation":[3,170,198,255],"are":[4,26,72],"both":[5,77,258],"important":[6],"tasks":[7,66,71,212],"in":[8,241,251],"recommender":[9],"systems.":[10],"Item":[11],"recommendation,":[12,38],"learning":[13,190],"user-item":[14],"rating":[15,127],"patterns,":[16],"helps":[17],"users":[18,44,84,94,220,237],"to":[19,29,45,101,135,152,164,171,213,231,253],"discover":[20],"a":[21,47,111,124,129,188,228,242],"list":[22,49],"of":[23,41,50,83,105,157,249,265],"items":[24,159,180,216,246,250],"that":[25,52,192],"more":[27],"likely":[28],"match":[30],"their":[31,56,137,178],"interests.":[32],"On":[33],"the":[34,92,102,207,263],"other":[35,88],"hand,":[36],"tag":[37,169,195],"exploiting":[39],"relationships":[40,240],"user-tag-item,":[42],"assists":[43],"find":[46],"personalized":[48,179],"tags":[51,100,151,161,218],"can":[53],"precisely":[54],"describe":[55],"experience":[57],"on":[58,119],"items.":[59,86,106,154],"Existing":[60],"methods":[61],"often":[62],"consider":[63],"these":[64,69],"two":[65,70,211],"independently.":[67],"However,":[68],"inherently":[73],"related":[74],"because":[75],"they":[76],"use":[78],"information":[79,235],"from":[80],"same":[81,93,103],"groups":[82],"In":[87,183,203],"words,":[89],"it":[90],"is":[91],"who":[95],"give":[96,123,145],"ratings":[97,147],"annotate":[99],"set":[104],"Tags":[107],"may":[108],"explain":[109],"why":[110],"user":[112],"purchase":[113],"an":[114],"item.":[115],"For":[116],"instance,":[117],"customers":[118],"Yelp":[120],"not":[121],"only":[122],"five":[125],"star":[126],"for":[128,219,257],"restaurant":[130],"but":[131],"also":[132,226],"leave":[133],"comments/tags":[134],"express":[136],"positive":[138],"sentiments.":[139],"Users":[140],"with":[141],"similar":[142,146,150],"interests":[143],"might":[144],"post":[149],"certain":[153],"The":[155],"co-occurrence":[156],"users,":[158],"motivates":[162],"us":[163],"jointly":[165],"perform":[166],"better":[172],"model":[173],"users'":[174,239],"behavior":[175],"by":[176],"leveraging":[177],"tags.":[182],"this":[184],"work,":[185],"we":[186,205],"propose":[187],"cross-domain":[189],"method":[191],"seamlessly":[193],"integrates":[194],"into":[199],"one":[200],"unified":[201],"framework.":[202],"particular,":[204],"utilize":[206],"knowledge":[208],"transferred":[209],"between":[210],"collaboratively":[214],"rank":[215],"through":[221],"coupled":[222],"tensor-matrix":[223],"factorization.":[224],"We":[225],"provide":[227],"principled":[229],"way":[230],"incorporate":[232],"additional":[233],"auxiliary":[234],"about":[236],"(e.g.,":[238,247],"social":[243],"network)":[244],"descriptions":[248],"Wikipedia)":[252],"improve":[254],"accuracy":[256],"tasks.":[259],"Empirical":[260],"results":[261],"demonstrate":[262],"effectiveness":[264],"our":[266],"proposed":[267],"model.":[268]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
