{"id":"https://openalex.org/W4312599622","doi":"https://doi.org/10.1109/tase.2022.3230783","title":"An Intention-Aware Markov Chain Based Method for Top-K Recommendation","display_name":"An Intention-Aware Markov Chain Based Method for Top-K Recommendation","publication_year":2022,"publication_date":"2022-12-22","ids":{"openalex":"https://openalex.org/W4312599622","doi":"https://doi.org/10.1109/tase.2022.3230783"},"language":"en","primary_location":{"id":"doi:10.1109/tase.2022.3230783","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2022.3230783","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","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/A5084071566","display_name":"Shiying Ni","orcid":"https://orcid.org/0000-0002-2889-0493"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiying Ni","raw_affiliation_strings":["Department of Industrial Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2889-0493","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031580282","display_name":"Shiyan Hu","orcid":"https://orcid.org/0000-0003-2512-0634"},"institutions":[{"id":"https://openalex.org/I43439940","display_name":"University of Southampton","ror":"https://ror.org/01ryk1543","country_code":"GB","type":"education","lineage":["https://openalex.org/I43439940"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shiyan Hu","raw_affiliation_strings":["School of Electronics and Computer Science, University of Southampton, Southampton, U.K"],"raw_orcid":"https://orcid.org/0000-0003-2512-0634","affiliations":[{"raw_affiliation_string":"School of Electronics and Computer Science, University of Southampton, Southampton, U.K","institution_ids":["https://openalex.org/I43439940"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021941275","display_name":"Lefei Li","orcid":"https://orcid.org/0000-0001-6816-6267"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lefei Li","raw_affiliation_strings":["Department of Industrial Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6816-6267","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1806,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.90420361,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"21","issue":"1","first_page":"581","last_page":"592"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9836000204086304,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9125999808311462,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7612060308456421},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.7500548362731934},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6389375925064087},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5861191749572754},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.49886298179626465},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.4719492495059967},{"id":"https://openalex.org/keywords/tuple","display_name":"Tuple","score":0.4698064923286438},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.46431490778923035},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.46275684237480164},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.45780205726623535},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4515100121498108},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.43241655826568604},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.42138487100601196},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4199259877204895},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4075450003147125},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3534680902957916},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.15937766432762146},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14179113507270813}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7612060308456421},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.7500548362731934},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6389375925064087},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5861191749572754},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.49886298179626465},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.4719492495059967},{"id":"https://openalex.org/C118930307","wikidata":"https://www.wikidata.org/wiki/Q600590","display_name":"Tuple","level":2,"score":0.4698064923286438},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.46431490778923035},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.46275684237480164},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.45780205726623535},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4515100121498108},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.43241655826568604},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.42138487100601196},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4199259877204895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4075450003147125},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3534680902957916},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.15937766432762146},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14179113507270813},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","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/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tase.2022.3230783","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2022.3230783","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6600000262260437}],"awards":[{"id":"https://openalex.org/G695161378","display_name":null,"funder_award_id":"2020AAA0103804","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W201521870","https://openalex.org/W1522301498","https://openalex.org/W1690919088","https://openalex.org/W1987431925","https://openalex.org/W1999047234","https://openalex.org/W2054141820","https://openalex.org/W2108920354","https://openalex.org/W2124591829","https://openalex.org/W2142144955","https://openalex.org/W2148810148","https://openalex.org/W2154908680","https://openalex.org/W2159094788","https://openalex.org/W2171279286","https://openalex.org/W2171960770","https://openalex.org/W2294005329","https://openalex.org/W2444485119","https://openalex.org/W2556522401","https://openalex.org/W2559084487","https://openalex.org/W2583674722","https://openalex.org/W2626454364","https://openalex.org/W2783272285","https://openalex.org/W2783666221","https://openalex.org/W2900697500","https://openalex.org/W2902040508","https://openalex.org/W2946777347","https://openalex.org/W2949340817","https://openalex.org/W2963367478","https://openalex.org/W2964296635","https://openalex.org/W2965744319","https://openalex.org/W2996931760","https://openalex.org/W2997310152","https://openalex.org/W3012772192","https://openalex.org/W3035642447","https://openalex.org/W3100480425","https://openalex.org/W3102619277","https://openalex.org/W3106181667","https://openalex.org/W3119242082","https://openalex.org/W3134722825","https://openalex.org/W3157278747","https://openalex.org/W3176302227","https://openalex.org/W3183820005","https://openalex.org/W3212204275","https://openalex.org/W4221141645","https://openalex.org/W4283373782","https://openalex.org/W4288083766","https://openalex.org/W4299286960","https://openalex.org/W6631190155","https://openalex.org/W6680830989","https://openalex.org/W6692935382","https://openalex.org/W6730169791"],"related_works":["https://openalex.org/W1484355083","https://openalex.org/W2772628444","https://openalex.org/W4220714703","https://openalex.org/W2735929803","https://openalex.org/W2170391450","https://openalex.org/W2098758514","https://openalex.org/W3008845055","https://openalex.org/W2041004656","https://openalex.org/W135044020","https://openalex.org/W4376854386"],"abstract_inverted_index":{"Recommender":[0],"systems":[1],"play":[2],"significant":[3],"roles":[4],"in":[5,8,145,178,343],"business,":[6],"especially":[7],"e-commerce.":[9],"Nevertheless,":[10],"users\u2019":[11],"behaviors":[12,49,224],"are":[13,198,225,280],"usually":[14],"mixing":[15,217],"and":[16,34,50,66,100,184,189,203,218,237,266,287,299,333,347,356],"drifting,":[17],"which":[18,161,232,279],"is":[19,85,109,143,159,209,292,341],"hard":[20],"to":[21,68,111,148,193,200,210],"tackle.":[22],"Current":[23],"sequential":[24,81,196,213],"methods":[25],"of":[26,36,47,64,92,97,120,180,263,277,285,297],"item-wise":[27],"interest":[28],"extracting":[29],"suffer":[30],"from":[31,215,310],"the":[32,70,89,95,105,113,118,121,150,212,216,257,261,274,290,303,307,311,335],"intricacy":[33],"sparsity":[35],"data.":[37],"Inspired":[38],"by":[39,228,241,282,314],"that":[40,171],"category-wise":[41],"interests":[42],"may":[43,53,233],"be":[44],"intrinsic":[45],"drivers":[46],"user":[48],"heterogeneous":[51],"actions":[52],"reveal":[54],"certain":[55],"behavior":[56],"patterns,":[57],"we":[58,125,243],"introduce":[59],"intention":[60,157,291,308],"as":[61,94,260,294,306],"a":[62,245,295,315,322],"tuple":[63,296],"category":[65,298],"action":[67],"address":[69],"data":[71],"issues.":[72],"In":[73,103],"this":[74,146],"paper,":[75],"an":[76,362],"intention-aware":[77,247],"Markov":[78,128,140,317,330],"chain":[79,129,141,331],"based":[80,130],"recommendation":[82,249,350,364],"model":[83,88,137,173,302,327,340,354,360],"(IMRec)":[84],"proposed.":[86],"We":[87,301,319],"overall":[90],"preferences":[91,99,259,265,272],"users":[93,286],"integration":[96,262],"long-term":[98,114,264,271],"short-term":[101,122,267,304],"intents.":[102,268],"particular,":[104],"matrix":[106],"factorization":[107],"method":[108,255,365],"adopted":[110],"extract":[112],"user-item":[115,220,258],"preference.":[116],"For":[117],"modeling":[119],"intents":[123,305],"transition,":[124],"adopt":[126],"high-order":[127,139,316,329],"methods.":[131],"A":[132,206],"factorized":[133],"mixture":[134,324],"transition":[135,309,325],"distribution":[136,326],"for":[138,328,370],"approximation":[142,332],"leveraged":[144],"paper":[147],"reduce":[149,334],"algorithm":[151,250,336],"complexity.":[152,337],"An":[153],"auxiliary":[154],"loss":[155],"on":[156,167],"representation":[158],"utilized,":[160],"brings":[162],"considerable":[163],"performance":[164,352],"improvements.":[165],"Experiments":[166],"real-world":[168,345],"datasets":[169,346],"demonstrate":[170],"our":[172],"outperforms":[174],"state-of-the-art":[175],"baseline":[176],"models":[177,256],"terms":[179],"three":[181],"common":[182],"metrics,":[183],"shows":[185,348],"superior":[186],"stability,":[187,353],"scalability,":[188,355],"training":[190,357],"efficiency.":[191,358],"Note":[192],"Practitioners\u2014In":[194],"e-commerce,":[195],"recommenders":[197],"essential":[199],"facilitate":[201],"decision-making":[202],"promote":[204],"business.":[205],"big":[207],"challenge":[208],"capture":[211],"patterns":[214],"drifting":[219],"interaction":[221],"sequences.":[222],"Customer":[223],"often":[226],"driven":[227],"their":[229],"inherent":[230],"intentions,":[231],"present":[234],"more":[235],"stable":[236],"reliable":[238],"patterns.":[239],"Motivated":[240],"that,":[242],"propose":[244],"novel":[246],"next-item":[248],"with":[251],"high":[252],"performance.":[253],"Our":[254,359],"More":[269],"specifically,":[270],"show":[273],"general":[275],"tastes":[276],"users,":[278],"modeled":[281],"latent":[283],"factors":[284],"items.":[288],"Additionally,":[289],"defined":[293],"action.":[300],"past":[312],"intentions":[313],"chain.":[318],"further":[320],"leverage":[321],"factorization-based":[323],"The":[338],"proposed":[339],"validated":[342],"4":[344],"good":[349],"performance,":[351],"provides":[361],"effective":[363],"at":[366],"low":[367],"computational":[368],"costs":[369],"e-commerce":[371],"companies.":[372]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}