{"id":"https://openalex.org/W2921645317","doi":"https://doi.org/10.1109/ai4i.2018.8665715","title":"Consumption Behavior Prediction Using Hierarchical Bayesian Frameworks","display_name":"Consumption Behavior Prediction Using Hierarchical Bayesian Frameworks","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2921645317","doi":"https://doi.org/10.1109/ai4i.2018.8665715","mag":"2921645317"},"language":"en","primary_location":{"id":"doi:10.1109/ai4i.2018.8665715","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ai4i.2018.8665715","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 First International Conference on Artificial Intelligence for Industries (AI4I)","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/A5060719711","display_name":"Nuha Zamzami","orcid":"https://orcid.org/0000-0001-9328-9218"},"institutions":[{"id":"https://openalex.org/I185163786","display_name":"King Abdulaziz University","ror":"https://ror.org/02ma4wv74","country_code":"SA","type":"education","lineage":["https://openalex.org/I185163786"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Nuha Zamzami","raw_affiliation_strings":["Paculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Paculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia","institution_ids":["https://openalex.org/I185163786"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090600716","display_name":"Nizar Bouguila","orcid":"https://orcid.org/0000-0001-7224-7940"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Nizar Bouguila","raw_affiliation_strings":["Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, QC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2905,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.93965667,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"382","issue":null,"first_page":"31","last_page":"34"},"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":0.9986000061035156,"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9905999898910522,"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/computer-science","display_name":"Computer science","score":0.7965582609176636},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.579303503036499},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5585612058639526},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5535293221473694},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5525578856468201},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5100656151771545},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46711859107017517},{"id":"https://openalex.org/keywords/consumption","display_name":"Consumption (sociology)","score":0.44994983077049255},{"id":"https://openalex.org/keywords/purchasing","display_name":"Purchasing","score":0.41400524973869324},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3373499810695648}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7965582609176636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.579303503036499},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5585612058639526},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5535293221473694},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5525578856468201},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5100656151771545},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46711859107017517},{"id":"https://openalex.org/C30772137","wikidata":"https://www.wikidata.org/wiki/Q5164762","display_name":"Consumption (sociology)","level":2,"score":0.44994983077049255},{"id":"https://openalex.org/C2778813691","wikidata":"https://www.wikidata.org/wiki/Q1369832","display_name":"Purchasing","level":2,"score":0.41400524973869324},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3373499810695648},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ai4i.2018.8665715","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ai4i.2018.8665715","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 First International Conference on Artificial Intelligence for Industries (AI4I)","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":33,"referenced_works":["https://openalex.org/W1197916086","https://openalex.org/W1573666180","https://openalex.org/W1987431925","https://openalex.org/W2008161828","https://openalex.org/W2023801818","https://openalex.org/W2033213271","https://openalex.org/W2054141820","https://openalex.org/W2068406209","https://openalex.org/W2100755716","https://openalex.org/W2110096996","https://openalex.org/W2110953678","https://openalex.org/W2117853077","https://openalex.org/W2123528936","https://openalex.org/W2124172487","https://openalex.org/W2135631383","https://openalex.org/W2137245235","https://openalex.org/W2143869282","https://openalex.org/W2144245426","https://openalex.org/W2159094788","https://openalex.org/W2219888463","https://openalex.org/W2339311053","https://openalex.org/W2418100820","https://openalex.org/W2604836762","https://openalex.org/W2767807341","https://openalex.org/W2801571361","https://openalex.org/W2807567715","https://openalex.org/W4298149265","https://openalex.org/W6634348268","https://openalex.org/W6680451568","https://openalex.org/W6716965457","https://openalex.org/W6735665619","https://openalex.org/W6750809063","https://openalex.org/W6751833777"],"related_works":["https://openalex.org/W2351217280","https://openalex.org/W2086836292","https://openalex.org/W2354083748","https://openalex.org/W2357949222","https://openalex.org/W2338005294","https://openalex.org/W2104192539","https://openalex.org/W2954733677","https://openalex.org/W2033865166","https://openalex.org/W2393625522","https://openalex.org/W1575721881"],"abstract_inverted_index":{"Purchasing":[0],"products,":[1],"listening":[2],"to":[3,83],"music,":[4],"visiting":[5],"locations":[6],"in":[7,48,88,100],"physical":[8],"or":[9],"virtual":[10],"environments":[11],"are":[12],"examples":[13],"of":[14,24,59,75,90],"applications":[15],"where":[16],"users":[17],"can":[18],"interact":[19],"with":[20],"a":[21,57],"large":[22],"set":[23],"items.":[25],"In":[26],"this":[27,69,113],"context,":[28],"making":[29],"predictions":[30,103],"for":[31,37,112],"both":[32],"previously-consumed":[33],"and":[34,71,92,108],"new":[35,44],"items":[36],"an":[38],"individual,":[39],"rather":[40],"than":[41],"just":[42],"recommending":[43],"items,":[45],"is":[46],"significant":[47],"many":[49],"situations.":[50],"A":[51],"recent":[52],"work":[53],"has":[54],"shown":[55],"that":[56],"mixture":[58],"Multinomials":[60],"outperforms":[61],"the":[62,73,96],"widely-used":[63],"matrix":[64],"factorization.":[65],"We":[66,94],"further":[67],"investigate":[68],"problem":[70],"propose":[72],"use":[74],"alternative":[76,97],"mixtures":[77],"based":[78],"on":[79],"hierarchical":[80],"Bayesian":[81],"frameworks":[82],"better":[84],"balance":[85],"individual":[86],"preferences":[87],"terms":[89],"exploitation":[91],"exploration.":[93],"evaluate":[95],"models":[98],"accuracy":[99],"user":[101],"consumption":[102],"using":[104],"several":[105],"real-world":[106],"datasets,":[107],"show":[109],"their":[110],"efficiency":[111],"problem.":[114]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}