{"id":"https://openalex.org/W4410398281","doi":"https://doi.org/10.32473/flairs.38.1.138970","title":"Flexible Dirichlet Mixture Model for Multi-modal data Clustering","display_name":"Flexible Dirichlet Mixture Model for Multi-modal data Clustering","publication_year":2025,"publication_date":"2025-05-14","ids":{"openalex":"https://openalex.org/W4410398281","doi":"https://doi.org/10.32473/flairs.38.1.138970"},"language":"en","primary_location":{"id":"doi:10.32473/flairs.38.1.138970","is_oa":true,"landing_page_url":"https://doi.org/10.32473/flairs.38.1.138970","pdf_url":"https://journals.flvc.org/FLAIRS/article/download/138970/144034","source":{"id":"https://openalex.org/S4210205383","display_name":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","issn_l":"2334-0754","issn":["2334-0754","2334-0762"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310320363","host_organization_name":"George A. Smathers Libraries","host_organization_lineage":["https://openalex.org/P4310320363"],"host_organization_lineage_names":["George A. Smathers Libraries"],"type":"conference"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The International FLAIRS Conference Proceedings","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://journals.flvc.org/FLAIRS/article/download/138970/144034","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076114384","display_name":"Seung-Hyun Hong","orcid":"https://orcid.org/0000-0003-2848-6666"},"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":true,"raw_author_name":"Seunghyun Hong","raw_affiliation_strings":["Concordia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Concordia University","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029366450","display_name":"Fatma Najar","orcid":"https://orcid.org/0000-0003-2301-4803"},"institutions":[{"id":"https://openalex.org/I174216632","display_name":"City University of New York","ror":"https://ror.org/00453a208","country_code":"US","type":"education","lineage":["https://openalex.org/I174216632"]},{"id":"https://openalex.org/I92507152","display_name":"John Jay College of Criminal Justice","ror":"https://ror.org/01p9rc392","country_code":"US","type":"education","lineage":["https://openalex.org/I92507152"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fatma Najar","raw_affiliation_strings":["John Jay College of Criminal Justice, The City University of New York"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"John Jay College of Criminal Justice, The City University of New York","institution_ids":["https://openalex.org/I92507152","https://openalex.org/I174216632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008962576","display_name":"Manar Amayri","orcid":"https://orcid.org/0000-0002-5610-8833"},"institutions":[{"id":"https://openalex.org/I161856759","display_name":"Concordia University","ror":"https://ror.org/01qxhf360","country_code":"US","type":"education","lineage":["https://openalex.org/I161856759"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manar Amayri","raw_affiliation_strings":["CIISE, Concordia University,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CIISE, Concordia University,","institution_ids":["https://openalex.org/I161856759"]}]},{"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/I161856759","display_name":"Concordia University","ror":"https://ror.org/01qxhf360","country_code":"US","type":"education","lineage":["https://openalex.org/I161856759"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nizar Bouguila","raw_affiliation_strings":["CIISE, Concordia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CIISE, Concordia University","institution_ids":["https://openalex.org/I161856759"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5076114384"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":1.4041,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.82439248,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"38","issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.960099995136261,"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"}},"topics":[{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.960099995136261,"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"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9599000215530396,"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/modal","display_name":"Modal","score":0.6158910989761353},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5909664034843445},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.5831514000892639},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.49761322140693665},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49525371193885803},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.4151465892791748},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.325425922870636},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.303805410861969},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2209978699684143},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.13965058326721191},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.13921454548835754}],"concepts":[{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.6158910989761353},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5909664034843445},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.5831514000892639},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.49761322140693665},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49525371193885803},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.4151465892791748},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.325425922870636},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.303805410861969},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2209978699684143},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.13965058326721191},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.13921454548835754},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.32473/flairs.38.1.138970","is_oa":true,"landing_page_url":"https://doi.org/10.32473/flairs.38.1.138970","pdf_url":"https://journals.flvc.org/FLAIRS/article/download/138970/144034","source":{"id":"https://openalex.org/S4210205383","display_name":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","issn_l":"2334-0754","issn":["2334-0754","2334-0762"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310320363","host_organization_name":"George A. Smathers Libraries","host_organization_lineage":["https://openalex.org/P4310320363"],"host_organization_lineage_names":["George A. Smathers Libraries"],"type":"conference"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The International FLAIRS Conference Proceedings","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:de277df5feef489a8570c7789ce013e1","is_oa":true,"landing_page_url":"https://doaj.org/article/de277df5feef489a8570c7789ce013e1","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":"Proceedings of the International Florida Artificial Intelligence Research Society Conference, Vol 38, Iss 1 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.32473/flairs.38.1.138970","is_oa":true,"landing_page_url":"https://doi.org/10.32473/flairs.38.1.138970","pdf_url":"https://journals.flvc.org/FLAIRS/article/download/138970/144034","source":{"id":"https://openalex.org/S4210205383","display_name":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","issn_l":"2334-0754","issn":["2334-0754","2334-0762"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310320363","host_organization_name":"George A. Smathers Libraries","host_organization_lineage":["https://openalex.org/P4310320363"],"host_organization_lineage_names":["George A. Smathers Libraries"],"type":"conference"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The International FLAIRS Conference Proceedings","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410398281.pdf","grobid_xml":"https://content.openalex.org/works/W4410398281.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3126382579","https://openalex.org/W3107650560","https://openalex.org/W2810542905","https://openalex.org/W2891616219","https://openalex.org/W2497860580","https://openalex.org/W3204672119","https://openalex.org/W1882901045","https://openalex.org/W3116791621","https://openalex.org/W74847246","https://openalex.org/W1511396599"],"abstract_inverted_index":{"Clustering":[0],"datasets":[1],"with":[2],"complex":[3],"structures,":[4],"such":[5],"as":[6],"multi-modal":[7,53,88],"properties":[8],"and":[9,41,52,66],"asymmetric":[10],"distributions,":[11],"presents":[12],"significant":[13],"challenges":[14],"in":[15],"data":[16,79,89],"analysis.":[17],"To":[18],"address":[19],"these":[20],"issues,":[21],"this":[22],"paper":[23],"introduces":[24],"the":[25,37,42,56,71,77,85],"Flexible":[26],"Dirichlet":[27],"Mixture":[28],"Model":[29],"(FDMM).":[30],"The":[31,61],"model":[32],"learning":[33],"is":[34,81],"accomplished":[35],"through":[36],"method":[38],"of":[39],"moments":[40],"expectation-maximization":[43],"(EM)":[44],"algorithm.":[45],"Empiricalevaluations":[46],"across":[47],"diverse":[48],"datasets,":[49],"including":[50],"unimodal":[51],"data,":[54],"demonstrate":[55],"model\u2019s":[57],"superior":[58,74],"clustering":[59],"performance.":[60],"results":[62],"confirm":[63],"FDMM\u2019s":[64],"adaptability":[65],"effectiveness.":[67],"We":[68],"find":[69],"that":[70],"FDMM":[72],"exhibits":[73],"performance":[75],"when":[76],"underlying":[78],"structure":[80],"complex,":[82],"compared":[83],"to":[84],"related-works":[86],"on":[87],"clustering.":[90]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-05-08T15:41:06.802602","created_date":"2025-10-10T00:00:00"}