{"id":"https://openalex.org/W3213487568","doi":"https://doi.org/10.1109/access.2021.3128769","title":"Personalized Preference Drift Aware Sequential Recommender System","display_name":"Personalized Preference Drift Aware Sequential Recommender System","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3213487568","doi":"https://doi.org/10.1109/access.2021.3128769","mag":"3213487568"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3128769","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3128769","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2021.3128769","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058221096","display_name":"Nakarin Sritrakool","orcid":"https://orcid.org/0000-0002-4364-8785"},"institutions":[{"id":"https://openalex.org/I158708052","display_name":"Chulalongkorn University","ror":"https://ror.org/028wp3y58","country_code":"TH","type":"education","lineage":["https://openalex.org/I158708052"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Nakarin Sritrakool","raw_affiliation_strings":["Advanced Virtual and Intelligent Computing Center, Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand. (e-mail: nakarin.s@math.sc.chula.ac.th)"],"raw_orcid":"https://orcid.org/0000-0002-4364-8785","affiliations":[{"raw_affiliation_string":"Advanced Virtual and Intelligent Computing Center, Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand. (e-mail: nakarin.s@math.sc.chula.ac.th)","institution_ids":["https://openalex.org/I158708052"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017525527","display_name":"Saranya Maneeroj","orcid":"https://orcid.org/0000-0003-3827-2549"},"institutions":[{"id":"https://openalex.org/I158708052","display_name":"Chulalongkorn University","ror":"https://ror.org/028wp3y58","country_code":"TH","type":"education","lineage":["https://openalex.org/I158708052"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Saranya Maneeroj","raw_affiliation_strings":["Advanced Virtual and Intelligent Computing Center, Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Virtual and Intelligent Computing Center, Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand","institution_ids":["https://openalex.org/I158708052"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5058221096"],"corresponding_institution_ids":["https://openalex.org/I158708052"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.844,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.92166221,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"9","issue":null,"first_page":"155491","last_page":"155506"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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":0.993399977684021,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9896000027656555,"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/preference","display_name":"Preference","score":0.8189756870269775},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7673954963684082},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.6299110651016235},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6181514263153076},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6167798638343811},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5046361684799194},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.4897587299346924},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.46788305044174194},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42624977231025696},{"id":"https://openalex.org/keywords/preference-learning","display_name":"Preference learning","score":0.4184098243713379},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10873672366142273},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08942791819572449},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07056564092636108}],"concepts":[{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.8189756870269775},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7673954963684082},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.6299110651016235},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6181514263153076},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6167798638343811},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5046361684799194},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.4897587299346924},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.46788305044174194},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42624977231025696},{"id":"https://openalex.org/C181204326","wikidata":"https://www.wikidata.org/wiki/Q7239820","display_name":"Preference learning","level":3,"score":0.4184098243713379},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10873672366142273},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08942791819572449},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07056564092636108},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3128769","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3128769","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3512a8adfa7643689c715f8fcc12f5a4","is_oa":true,"landing_page_url":"https://doaj.org/article/3512a8adfa7643689c715f8fcc12f5a4","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 155491-155506 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3128769","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3128769","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4000000059604645,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W1500188831","https://openalex.org/W1522301498","https://openalex.org/W1677182931","https://openalex.org/W1720514416","https://openalex.org/W1994389483","https://openalex.org/W2054141820","https://openalex.org/W2064675550","https://openalex.org/W2080320419","https://openalex.org/W2095705004","https://openalex.org/W2113076747","https://openalex.org/W2157331557","https://openalex.org/W2167383409","https://openalex.org/W2253995343","https://openalex.org/W2471920251","https://openalex.org/W2509893387","https://openalex.org/W2510317721","https://openalex.org/W2583674722","https://openalex.org/W2605350416","https://openalex.org/W2625746539","https://openalex.org/W2626454364","https://openalex.org/W2739805805","https://openalex.org/W2749348810","https://openalex.org/W2750004028","https://openalex.org/W2767724106","https://openalex.org/W2783272285","https://openalex.org/W2783666221","https://openalex.org/W2788376297","https://openalex.org/W2792764867","https://openalex.org/W2793768763","https://openalex.org/W2893359107","https://openalex.org/W2896457183","https://openalex.org/W2913795167","https://openalex.org/W2917898551","https://openalex.org/W2950894652","https://openalex.org/W2951305674","https://openalex.org/W2963085847","https://openalex.org/W2963367478","https://openalex.org/W2964289984","https://openalex.org/W2984100107","https://openalex.org/W3035382476","https://openalex.org/W3037556679","https://openalex.org/W3098231197","https://openalex.org/W3099732023","https://openalex.org/W3102619277","https://openalex.org/W3102895136","https://openalex.org/W3104030692","https://openalex.org/W3106181667","https://openalex.org/W3180367960","https://openalex.org/W4288083766","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6674330103","https://openalex.org/W6729216784","https://openalex.org/W6739901393","https://openalex.org/W6749825310","https://openalex.org/W6755207826","https://openalex.org/W6760021316","https://openalex.org/W6766116973","https://openalex.org/W6779372110","https://openalex.org/W6780226713"],"related_works":["https://openalex.org/W2937325523","https://openalex.org/W257970033","https://openalex.org/W4205377104","https://openalex.org/W1994181006","https://openalex.org/W2911102221","https://openalex.org/W4281387587","https://openalex.org/W2943672508","https://openalex.org/W4320918405","https://openalex.org/W4383737174","https://openalex.org/W4285602503"],"abstract_inverted_index":{"The":[0,134,213],"user":[1,16,29,44,89,104,117,166,207],"preference":[2,17,30,45,90,105,118,153,167,176],"patterns":[3,31,46,58,119,177],"are":[4],"highly":[5],"dynamic":[6],"and":[7,37,49],"develop":[8],"over":[9],"time.":[10],"To":[11],"address":[12],"the":[13,21,28,41,56,61,70,75,81,87,113,122,125,131,142,160,164,172,181,187,191,201,206,211,223,230,242,247],"drift":[14,57,64,102,115,136,208],"of":[15,20,43,60,103,116,127,179,193],"patterns,":[18,34,106],"most":[19],"prior":[22],"works":[23,68],"for":[24,51,210],"sequential":[25],"recommendation":[26],"categorize":[27],"into":[32,145],"different":[33],"e.g.,":[35],"short-term":[36],"long-term":[38],"preference.":[39],"However,":[40],"number":[42],"is":[47],"pre-defined":[48],"identical":[50],"every":[52],"user,":[53],"resulting":[54],"in":[55,124],"regardless":[59],"user\u2019s":[62],"actual":[63,114],"points.":[65],"Moreover,":[66],"existing":[67],"recommend":[69],"next":[71],"item":[72],"by":[73,120,169,197],"considering":[74,170,240],"whole":[76,182,248],"historical":[77,132,143,183],"sequence,":[78],"which":[79,148],"contains":[80],"noises":[82],"from":[83],"interactions":[84],"irrelevant":[85],"to":[86,99,140,163,189,204],"current":[88,165],"pattern.":[91,154],"In":[92],"this":[93],"work,":[94],"we":[95],"propose":[96],"a":[97,151,156],"model":[98,205],"personalized":[100],"detects":[101],"called":[107],"PPD.":[108],"Our":[109],"proposed":[110,195,219],"method":[111,196,220],"determines":[112],"capturing":[121],"changes":[123],"characteristics":[126],"consecutive":[128],"items":[129],"throughout":[130],"sequence.":[133,184,249],"detected":[135],"pattern":[137,168,209],"allows":[138],"PPD":[139,158,199,235],"partition":[141],"sequence":[144],"various":[146],"sub-sequences":[147,173],"contain":[149],"only":[150,171,241],"particular":[152],"As":[155],"result,":[157],"delivers":[159,236],"recommendations":[161],"relevant":[162,243],"with":[174,200],"similar":[175],"instead":[178],"utilizing":[180],"We":[185],"conduct":[186],"experiments":[188],"verify":[190],"effectiveness":[192],"our":[194,218],"comparing":[198],"baselines":[202,224],"aiming":[203],"recommendation.":[212],"experimental":[214],"results":[215,238],"show":[216],"that":[217,234],"consistently":[221],"outperforms":[222],"on":[225],"three":[226],"benchmark":[227],"datasets.":[228],"Additionally,":[229],"experiment":[231],"further":[232],"shows":[233],"superior":[237],"when":[239],"periods":[244],"rather":[245],"than":[246]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
