{"id":"https://openalex.org/W2087039765","doi":"https://doi.org/10.1145/2808194.2809459","title":"A Theoretical Analysis of Two-Stage Recommendation for Cold-Start Collaborative Filtering","display_name":"A Theoretical Analysis of Two-Stage Recommendation for Cold-Start Collaborative Filtering","publication_year":2015,"publication_date":"2015-09-22","ids":{"openalex":"https://openalex.org/W2087039765","doi":"https://doi.org/10.1145/2808194.2809459","mag":"2087039765"},"language":"en","primary_location":{"id":"doi:10.1145/2808194.2809459","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2808194.2809459","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 Conference on The Theory of Information Retrieval","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/A5101807932","display_name":"Xiaoxue Zhao","orcid":"https://orcid.org/0000-0002-1358-2228"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Xiaoxue Zhao","raw_affiliation_strings":["University College London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"University College London, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100384727","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0002-4021-4228"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["University College London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"University College London, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101807932"],"corresponding_institution_ids":["https://openalex.org/I45129253"],"apc_list":null,"apc_paid":null,"fwci":0.7946,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.80927159,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"71","last_page":"80"},"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9955000281333923,"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"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/collaborative-filtering","display_name":"Collaborative filtering","score":0.8644338846206665},{"id":"https://openalex.org/keywords/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.8527920246124268},{"id":"https://openalex.org/keywords/movielens","display_name":"MovieLens","score":0.8476275205612183},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8074778318405151},{"id":"https://openalex.org/keywords/cold-start","display_name":"Cold start (automotive)","score":0.6659919023513794},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.562931478023529},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.558667004108429},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.49730637669563293},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.41711103916168213},{"id":"https://openalex.org/keywords/stage","display_name":"Stage (stratigraphy)","score":0.41643714904785156},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.39880675077438354},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38206782937049866},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36443090438842773},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3040921688079834},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.23820513486862183},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11074039340019226},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07235011458396912}],"concepts":[{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.8644338846206665},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.8527920246124268},{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.8476275205612183},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8074778318405151},{"id":"https://openalex.org/C2778956030","wikidata":"https://www.wikidata.org/wiki/Q5142477","display_name":"Cold start (automotive)","level":2,"score":0.6659919023513794},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.562931478023529},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.558667004108429},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.49730637669563293},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.41711103916168213},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.41643714904785156},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.39880675077438354},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38206782937049866},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36443090438842773},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3040921688079834},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.23820513486862183},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11074039340019226},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07235011458396912},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2808194.2809459","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2808194.2809459","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 Conference on The Theory of Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W281665770","https://openalex.org/W1488971269","https://openalex.org/W1501049730","https://openalex.org/W1532852017","https://openalex.org/W1687468423","https://openalex.org/W1854214752","https://openalex.org/W1880262756","https://openalex.org/W1994389483","https://openalex.org/W2013221919","https://openalex.org/W2014050279","https://openalex.org/W2018571751","https://openalex.org/W2032100464","https://openalex.org/W2042281163","https://openalex.org/W2048045485","https://openalex.org/W2049455633","https://openalex.org/W2054141820","https://openalex.org/W2054675234","https://openalex.org/W2065663334","https://openalex.org/W2076214575","https://openalex.org/W2085937320","https://openalex.org/W2091780923","https://openalex.org/W2095852781","https://openalex.org/W2100235918","https://openalex.org/W2106365165","https://openalex.org/W2108114251","https://openalex.org/W2108168165","https://openalex.org/W2110325612","https://openalex.org/W2113922211","https://openalex.org/W2117281325","https://openalex.org/W2119490247","https://openalex.org/W2126695993","https://openalex.org/W2127186087","https://openalex.org/W2137245235","https://openalex.org/W2142144955","https://openalex.org/W2148933855","https://openalex.org/W2149822245","https://openalex.org/W2155201359","https://openalex.org/W2158515176","https://openalex.org/W2164354502","https://openalex.org/W2168359464","https://openalex.org/W2168405694","https://openalex.org/W2170518359","https://openalex.org/W2171960770","https://openalex.org/W2317700292","https://openalex.org/W2499002200","https://openalex.org/W4229651205","https://openalex.org/W4232980324","https://openalex.org/W4245920622"],"related_works":["https://openalex.org/W2355698112","https://openalex.org/W2022984797","https://openalex.org/W4394818607","https://openalex.org/W2986679525","https://openalex.org/W2797500822","https://openalex.org/W2794458286","https://openalex.org/W4205822456","https://openalex.org/W4299358966","https://openalex.org/W2954356050","https://openalex.org/W3002169615"],"abstract_inverted_index":{"In":[0,103],"this":[1,104,192],"paper,":[2,105],"we":[3,60,106,149,194],"present":[4],"a":[5,29,48,108,113,116],"theoretical":[6,220],"framework":[7],"for":[8,88,187],"tackling":[9],"the":[10,24,56,67,75,90,101,123,126,144,168,172,188,201,204,214],"cold-start":[11],"collaborative":[12],"filtering":[13],"problem,":[14],"where":[15],"unknown":[16],"targets":[17],"(items":[18],"or":[19,35,181],"users)":[20],"keep":[21],"coming":[22],"to":[23,43,82,95,167,171,199],"system,":[25],"and":[26,41,52,115,133,213,222],"there":[27],"is":[28,79],"limited":[30,57],"number":[31],"of":[32,203],"resources":[33,70,84,160,186],"(users":[34],"items)":[36],"that":[37,85,151,161],"can":[38,155],"be":[39,156],"allocated":[40],"related":[42],"them.":[44],"The":[45],"solution":[46,118,154,198],"requires":[47],"trade-off":[49],"between":[50],"exploitation":[51],"exploration":[53],"since":[54],"with":[55,125,183],"recommendation":[58,111],"opportunities,":[59],"need":[61],"to,":[62],"on":[63,74,210],"one":[64],"hand,":[65,77],"allocate":[66,83],"most":[68],"relevant":[69,98,166],"right":[71],"away,":[72],"but,":[73],"other":[76,184],"it":[78],"also":[80,176],"necessary":[81],"are":[86,162],"useful":[87],"learning":[89],"target's":[91],"properties":[92],"in":[93,100],"order":[94],"recommend":[96],"more":[97],"ones":[99],"future.":[102],"study":[107],"simple":[109],"two-stage":[110],"combining":[112],"sequential":[114],"batch":[117],"together.":[119],"We":[120],"first":[121],"model":[122],"problem":[124],"partially":[127],"observable":[128],"Markov":[129],"decision":[130],"process":[131],"(POMDP)":[132],"provide":[134],"its":[135],"exact":[136,153,205],"solution.":[137,206],"Then,":[138],"through":[139],"an":[140,152,196],"in-depth":[141],"analysis":[142],"over":[143],"POMDP":[145],"value":[146],"iteration":[147],"solution,":[148],"identify":[150],"abstracted":[157],"as":[158],"selecting":[159],"not":[163],"only":[164],"highly":[165,177],"target":[169],"according":[170],"initial-stage":[173],"information,":[174],"but":[175],"correlated,":[178],"either":[179],"positively":[180],"negatively,":[182],"potential":[185],"next":[189],"stage.":[190],"With":[191],"finding,":[193],"propose":[195],"approximate":[197],"ease":[200],"intractability":[202],"Our":[207],"initial":[208],"results":[209],"synthetic":[211],"data":[212],"MovieLens":[215],"100K":[216],"dataset":[217],"confirm":[218],"our":[219],"development":[221],"analysis.":[223]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
