{"id":"https://openalex.org/W4391093095","doi":"https://doi.org/10.1109/bigdata59044.2023.10386644","title":"Harnessing Behavioral Traits to Enhance Financial Stock Recommender Systems: Tackling the User Cold Start Problem","display_name":"Harnessing Behavioral Traits to Enhance Financial Stock Recommender Systems: Tackling the User Cold Start Problem","publication_year":2023,"publication_date":"2023-12-15","ids":{"openalex":"https://openalex.org/W4391093095","doi":"https://doi.org/10.1109/bigdata59044.2023.10386644"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata59044.2023.10386644","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata59044.2023.10386644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","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/A5074574419","display_name":"Takehiro Takayanagi","orcid":"https://orcid.org/0009-0000-6467-8222"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takehiro Takayanagi","raw_affiliation_strings":["The University of Tokyo,School of Engineering,Tokyo,Japan","School of Engineering, The University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,School of Engineering,Tokyo,Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"School of Engineering, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044205949","display_name":"Kiyoshi Izumi","orcid":"https://orcid.org/0000-0003-0870-7310"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kiyoshi Izumi","raw_affiliation_strings":["The University of Tokyo,School of Engineering,Tokyo,Japan","School of Engineering, The University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,School of Engineering,Tokyo,Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"School of Engineering, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.33580151,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5694","last_page":"5703"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9986000061035156,"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":0.9986000061035156,"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":0.9975000023841858,"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.7738483548164368},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6502375602722168},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.5261984467506409},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3785407543182373},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.31983858346939087},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14459839463233948}],"concepts":[{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7738483548164368},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6502375602722168},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.5261984467506409},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3785407543182373},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.31983858346939087},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14459839463233948},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata59044.2023.10386644","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata59044.2023.10386644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W2009415795","https://openalex.org/W2036740855","https://openalex.org/W2071559616","https://openalex.org/W2095705004","https://openalex.org/W2101409192","https://openalex.org/W2134088756","https://openalex.org/W2138053063","https://openalex.org/W2161080627","https://openalex.org/W2162090451","https://openalex.org/W2169219194","https://openalex.org/W2200151863","https://openalex.org/W2221222813","https://openalex.org/W2268996352","https://openalex.org/W2502832733","https://openalex.org/W2753686090","https://openalex.org/W2776933647","https://openalex.org/W2883381738","https://openalex.org/W2893902841","https://openalex.org/W2933316466","https://openalex.org/W2949676527","https://openalex.org/W3044498809","https://openalex.org/W3045200674","https://openalex.org/W3081484165","https://openalex.org/W3102896162","https://openalex.org/W3123119769","https://openalex.org/W3167332654","https://openalex.org/W3199328271","https://openalex.org/W4226160027","https://openalex.org/W4236670843","https://openalex.org/W4288083766","https://openalex.org/W4296604405","https://openalex.org/W4384661031","https://openalex.org/W4384895115","https://openalex.org/W4387212059","https://openalex.org/W4392143762","https://openalex.org/W6674330103","https://openalex.org/W6744107841"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405","https://openalex.org/W2056712470","https://openalex.org/W3125580266"],"abstract_inverted_index":{"Recommender":[0],"systems":[1],"often":[2,35],"struggle":[3],"with":[4,77],"the":[5,57,84,119],"user":[6,85],"cold":[7,86,140],"start":[8,87,141],"problem,":[9],"which":[10],"arises":[11],"when":[12],"there":[13],"is":[14,25],"a":[15,70,95,113],"lack":[16,36],"of":[17,59,148],"interaction":[18],"data":[19,111],"for":[20,136],"new":[21],"users.":[22,46],"This":[23],"issue":[24],"particularly":[26],"important":[27],"in":[28,112,139,156],"financial":[29,78],"stock":[30,79,137,159],"recommendations,":[31],"as":[32],"novice":[33],"investors":[34,101],"investment":[37],"experience":[38],"and":[39,55,125],"require":[40],"personalized":[41],"advice":[42],"more":[43,157],"than":[44],"experienced":[45],"Behavioral":[47],"finance":[48,76],"offers":[49],"valuable":[50],"insights":[51],"into":[52],"investor":[53,63],"preferences":[54],"highlights":[56],"impact":[58],"psychological":[60],"factors":[61],"on":[62],"behavior.":[64],"In":[65],"this":[66],"paper,":[67],"we":[68,92,117,144],"present":[69],"novel":[71],"framework":[72],"that":[73,90],"integrates":[74],"behavioral":[75,105,152],"recommendations":[80,138],"to":[81,102],"effectively":[82],"tackle":[83],"problem.":[88],"To":[89],"end,":[91],"first":[93],"conduct":[94],"survey":[96],"involving":[97],"964":[98],"Japanese":[99],"individual":[100],"gather":[103],"investment-related":[104],"traits":[106,153],"while":[107],"collecting":[108],"their":[109],"transaction":[110],"trading":[114],"platform.":[115],"Then,":[116],"introduce":[118],"Investor":[120],"Risk-tolerance":[121],"Aware":[122],"DropoutNet":[123],"(IRAD)":[124],"show":[126],"its":[127,134],"improved":[128],"performance":[129],"over":[130],"baseline":[131],"models,":[132],"demonstrating":[133],"effectiveness":[135],"settings.":[142],"Finally,":[143],"offer":[145],"an":[146],"example":[147],"how":[149],"incorporating":[150],"investors\u2019":[151],"can":[154],"result":[155],"interpretable":[158],"recommendations.":[160]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}