{"id":"https://openalex.org/W3162436086","doi":"https://doi.org/10.1109/mmul.2021.3077915","title":"Multimodal Semantics-Based Supervised Latent Dirichlet Allocation for Event Classification","display_name":"Multimodal Semantics-Based Supervised Latent Dirichlet Allocation for Event Classification","publication_year":2021,"publication_date":"2021-05-11","ids":{"openalex":"https://openalex.org/W3162436086","doi":"https://doi.org/10.1109/mmul.2021.3077915","mag":"3162436086"},"language":"en","primary_location":{"id":"doi:10.1109/mmul.2021.3077915","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmul.2021.3077915","pdf_url":null,"source":{"id":"https://openalex.org/S72873717","display_name":"IEEE Multimedia","issn_l":"1070-986X","issn":["1070-986X","1941-0166"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 MultiMedia","raw_type":"journal-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/A5014050181","display_name":"Naiyang Miao","orcid":null},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Naiyang Miao","raw_affiliation_strings":["Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Ministry of Education, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Ministry of Education, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081427161","display_name":"Feng Xue","orcid":"https://orcid.org/0000-0003-4962-9734"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Xue","raw_affiliation_strings":["Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Ministry of Education, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Ministry of Education, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051332325","display_name":"Richang Hong","orcid":"https://orcid.org/0000-0001-5461-3986"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Richang Hong","raw_affiliation_strings":["Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Ministry of Education, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Ministry of Education, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5014050181"],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":null,"apc_paid":null,"fwci":0.7789,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.70585337,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"28","issue":"4","first_page":"8","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.991599977016449,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9789999723434448,"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/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.8915189504623413},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.817878246307373},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.7480630278587341},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6905466318130493},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.595527708530426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5436139106750488},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5189756751060486},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5035178065299988},{"id":"https://openalex.org/keywords/distributional-semantics","display_name":"Distributional semantics","score":0.48628413677215576},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.44177013635635376},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4234943687915802},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.4134477972984314},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.22328776121139526}],"concepts":[{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.8915189504623413},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.817878246307373},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.7480630278587341},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6905466318130493},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.595527708530426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5436139106750488},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5189756751060486},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5035178065299988},{"id":"https://openalex.org/C2778828372","wikidata":"https://www.wikidata.org/wiki/Q5283209","display_name":"Distributional semantics","level":3,"score":0.48628413677215576},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.44177013635635376},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4234943687915802},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.4134477972984314},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.22328776121139526},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mmul.2021.3077915","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmul.2021.3077915","pdf_url":null,"source":{"id":"https://openalex.org/S72873717","display_name":"IEEE Multimedia","issn_l":"1070-986X","issn":["1070-986X","1941-0166"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 MultiMedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G3764158466","display_name":null,"funder_award_id":"61772170","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1973897992","https://openalex.org/W1984223097","https://openalex.org/W1995613787","https://openalex.org/W1998724497","https://openalex.org/W2044562039","https://openalex.org/W2059503458","https://openalex.org/W2063658521","https://openalex.org/W2098062695","https://openalex.org/W2100931213","https://openalex.org/W2106277773","https://openalex.org/W2122683976","https://openalex.org/W2147946282","https://openalex.org/W2151751257","https://openalex.org/W2169279737","https://openalex.org/W2587648059","https://openalex.org/W2787002882","https://openalex.org/W2904414472","https://openalex.org/W2983366375","https://openalex.org/W4233135949","https://openalex.org/W4237791300","https://openalex.org/W6675195331","https://openalex.org/W6682044806"],"related_works":["https://openalex.org/W2769501189","https://openalex.org/W4315588616","https://openalex.org/W4312773271","https://openalex.org/W2888805565","https://openalex.org/W2207653751","https://openalex.org/W2611137333","https://openalex.org/W3005513013","https://openalex.org/W4317422773","https://openalex.org/W4291700620","https://openalex.org/W3159709618"],"abstract_inverted_index":{"Social":[0],"event":[1,17,22],"classification":[2,23,121],"has":[3],"always":[4],"been":[5],"a":[6,49],"research":[7],"topic":[8,52],"of":[9,15,63,68,79,84,87,95,120,126,133],"great":[10],"interest":[11],"in":[12],"the":[13,38,85,88,92,106,118,131],"field":[14],"social":[16,21],"analysis.":[18],"In":[19,44],"existing":[20],"methods,":[24],"although":[25],"some":[26],"researchers":[27],"consciously":[28],"use":[29,83],"external":[30],"semantics":[31,70,86,94],"to":[32,130],"improve":[33],"model":[34,53,76],"performance,":[35],"they":[36],"ignore":[37],"more":[39],"easily":[40],"available":[41],"internal":[42,64],"semantics.":[43,73],"this":[45],"article,":[46],"we":[47],"propose":[48],"multimodal":[50,96],"supervised":[51,97],"based":[54],"on":[55,117],"semantic":[56,135],"weighting":[57],"(Sem-MMSTM),":[58],"which":[59],"uses":[60],"two":[61],"kinds":[62],"semantics,":[65],"namely":[66],"part":[67],"speech":[69],"and":[71,81,91,124],"category":[72,93],"Our":[74],"Sem-MMSTM":[75,111],"is":[77],"capable":[78],"mining":[80],"making":[82],"text":[89],"itself":[90],"corpus.":[98],"The":[99],"experimental":[100],"results":[101],"show":[102],"that,":[103],"compared":[104],"with":[105],"state-of-the-art":[107],"model,":[108],"our":[109],"proposed":[110],"yields":[112],"significant":[113],"performance":[114],"improvement":[115],"both":[116],"metrics":[119],"accuracy":[122],"(ACC)":[123],"interpretability":[125],"topics":[127],"(PMI)":[128],"due":[129],"introduction":[132],"effective":[134],"information.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
