{"id":"https://openalex.org/W4399146957","doi":"https://doi.org/10.1145/3659211.3659242","title":"Research on Interactive Advertising Strategies Using Machine Learning Algorithms for User Behavior Analysis","display_name":"Research on Interactive Advertising Strategies Using Machine Learning Algorithms for User Behavior Analysis","publication_year":2023,"publication_date":"2023-12-08","ids":{"openalex":"https://openalex.org/W4399146957","doi":"https://doi.org/10.1145/3659211.3659242"},"language":"en","primary_location":{"id":"doi:10.1145/3659211.3659242","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3659211.3659242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 4th International Conference on Big Data Economy and Information Management","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/A5002998542","display_name":"Jiaquan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiaquan Liu","raw_affiliation_strings":["School of journalism &amp; communication shanghai university, China"],"affiliations":[{"raw_affiliation_string":"School of journalism &amp; communication shanghai university, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033683433","display_name":"Haijun Yang","orcid":"https://orcid.org/0009-0004-8423-7335"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haijun Yang","raw_affiliation_strings":["School of journalism &amp; communication shanghai university, China"],"affiliations":[{"raw_affiliation_string":"School of journalism &amp; communication shanghai university, China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5002998542"],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":null,"apc_paid":null,"fwci":0.5798,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.79677911,"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":"181","last_page":"184"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10609","display_name":"Digital Marketing and Social Media","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10609","display_name":"Digital Marketing and Social Media","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/T10068","display_name":"Technology Adoption and User Behaviour","score":0.9690999984741211,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"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/T12659","display_name":"Innovation Diffusion and Forecasting","score":0.9553999900817871,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8298723697662354},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8078890442848206},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5998482704162598},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5513661503791809},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5513076186180115},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5505321025848389},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5236344337463379},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48558276891708374},{"id":"https://openalex.org/keywords/user-modeling","display_name":"User modeling","score":0.4640442728996277},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.441193550825119},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42435795068740845},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4195926785469055},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4176764488220215},{"id":"https://openalex.org/keywords/user-interface","display_name":"User interface","score":0.12717241048812866}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8298723697662354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8078890442848206},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5998482704162598},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5513661503791809},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5513076186180115},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5505321025848389},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5236344337463379},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48558276891708374},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.4640442728996277},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.441193550825119},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42435795068740845},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4195926785469055},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4176764488220215},{"id":"https://openalex.org/C89505385","wikidata":"https://www.wikidata.org/wiki/Q47146","display_name":"User interface","level":2,"score":0.12717241048812866},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3659211.3659242","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3659211.3659242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 4th International Conference on Big Data Economy and Information Management","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":5,"referenced_works":["https://openalex.org/W3211083900","https://openalex.org/W4224081503","https://openalex.org/W4225138632","https://openalex.org/W4285118875","https://openalex.org/W4320004216"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Based":[0],"on":[1,49,55],"the":[2,82,112,115,121,124,135,147,156],"collection":[3],"of":[4,30,114,127,137,149,158],"user":[5,32,37,56,95,107],"behavior":[6],"logs":[7],"and":[8,18,34,63,98,130,142,153],"multi-source":[9],"feature":[10,57],"representation,":[11],"this":[12,40],"study":[13],"integrates":[14],"convolutional":[15],"neural":[16,20],"networks":[17,21],"recurrent":[19],"to":[22,59,79],"establish":[23],"deep":[24,128],"learning":[25,51,86,129,132],"models,":[26],"achieving":[27],"accurate":[28],"mining":[29],"personalized":[31,84,150],"interests":[33],"constructing":[35],"high-quality":[36],"profiles.":[38],"On":[39],"basis,":[41],"a":[42,104],"dynamic":[43,64],"advertising":[44,87],"strategy":[45],"generation":[46],"mechanism":[47],"based":[48],"reinforcement":[50,85,131],"is":[52],"introduced,":[53],"relying":[54],"states":[58],"achieve":[60],"precise":[61],"targeting":[62],"optimization":[65],"adjustments,":[66],"resulting":[67],"in":[68,94,134],"higher":[69],"conversion":[70],"levels.":[71],"Simulation":[72],"environment":[73],"test":[74],"results":[75],"show":[76],"that":[77],"compared":[78],"traditional":[80],"techniques,":[81],"constructed":[83],"matching":[88],"system":[89],"has":[90],"made":[91],"significant":[92],"progress":[93],"profile":[96],"extraction":[97],"decision":[99],"tuning.":[100],"Empirical":[101],"evidence":[102],"from":[103],"video":[105],"website":[106],"log":[108],"case":[109],"further":[110],"validates":[111],"effectiveness":[113],"method.":[116],"This":[117],"research":[118],"explores":[119],"for":[120,145],"first":[122],"time":[123],"innovative":[125],"integration":[126],"technologies":[133],"field":[136],"interactive":[138],"advertising,":[139],"providing":[140],"theoretical":[141],"technical":[143],"support":[144],"solving":[146],"challenge":[148],"precision":[151],"recommendations":[152],"significantly":[154],"improving":[155],"level":[157],"related":[159],"systems,":[160],"with":[161],"broad":[162],"application":[163],"prospects.":[164]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
