{"id":"https://openalex.org/W4392939879","doi":"https://doi.org/10.1109/tmm.2024.3378173","title":"Graph-Based Multimodal Topic Modeling With Word Relations and Object Relations","display_name":"Graph-Based Multimodal Topic Modeling With Word Relations and Object Relations","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4392939879","doi":"https://doi.org/10.1109/tmm.2024.3378173"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2024.3378173","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tmm.2024.3378173","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Transactions on 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/A5043915187","display_name":"Bingshan Zhu","orcid":"https://orcid.org/0000-0002-8900-5662"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingshan Zhu","raw_affiliation_strings":["School of Engineering, South China University of Technology, Guangzhou, China","Key Laboratory of Big Data and Intelligent Robot (South China University of Technology), Ministry of Education, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-8900-5662","affiliations":[{"raw_affiliation_string":"School of Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Key Laboratory of Big Data and Intelligent Robot (South China University of Technology), Ministry of Education, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089123257","display_name":"Yi Cai","orcid":"https://orcid.org/0000-0002-1767-789X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Cai","raw_affiliation_strings":["School of Engineering, South China University of Technology, Guangzhou, China","Key Laboratory of Big Data and Intelligent Robot (South China University of Technology), Ministry of Education, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-1767-789X","affiliations":[{"raw_affiliation_string":"School of Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Key Laboratory of Big Data and Intelligent Robot (South China University of Technology), Ministry of Education, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002191673","display_name":"Jiexin Wang","orcid":"https://orcid.org/0000-0002-7064-6507"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiexin Wang","raw_affiliation_strings":["School of Engineering, South China University of Technology, Guangzhou, China","Key Laboratory of Big Data and Intelligent Robot (South China University of Technology), Ministry of Education, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7064-6507","affiliations":[{"raw_affiliation_string":"School of Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Key Laboratory of Big Data and Intelligent Robot (South China University of Technology), Ministry of Education, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.5557,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68855172,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"26","issue":null,"first_page":"8210","last_page":"8225"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9599999785423279,"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/T10028","display_name":"Topic Modeling","score":0.9599999785423279,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9513999819755554,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9370999932289124,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8603107333183289},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5409979820251465},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5254194736480713},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48161929845809937},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.339341938495636},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.27118951082229614}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8603107333183289},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5409979820251465},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5254194736480713},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48161929845809937},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.339341938495636},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27118951082229614}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2024.3378173","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tmm.2024.3378173","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5840809434","display_name":null,"funder_award_id":"x2rjD2230080","funder_id":"https://openalex.org/F4320323059","funder_display_name":"South China University of Technology"},{"id":"https://openalex.org/G8189774080","display_name":null,"funder_award_id":"62076100","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8718620462","display_name":null,"funder_award_id":"2020B0101100002","funder_id":"https://openalex.org/F4320335795","funder_display_name":"Science and Technology Planning Project of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323059","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null},{"id":"https://openalex.org/F4320335795","display_name":"Science and Technology Planning Project of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W91766825","https://openalex.org/W1950831375","https://openalex.org/W2001082470","https://openalex.org/W2006031689","https://openalex.org/W2007972815","https://openalex.org/W2020842694","https://openalex.org/W2025147484","https://openalex.org/W2036124047","https://openalex.org/W2046945311","https://openalex.org/W2048195127","https://openalex.org/W2050103272","https://openalex.org/W2060724430","https://openalex.org/W2106277773","https://openalex.org/W2129004009","https://openalex.org/W2151103935","https://openalex.org/W2161050705","https://openalex.org/W2181691731","https://openalex.org/W2189360217","https://openalex.org/W2250753706","https://openalex.org/W2294978630","https://openalex.org/W2405811584","https://openalex.org/W2530645150","https://openalex.org/W2549688307","https://openalex.org/W2600067905","https://openalex.org/W2727712598","https://openalex.org/W2787002882","https://openalex.org/W2793664262","https://openalex.org/W2896457183","https://openalex.org/W2897470545","https://openalex.org/W2908300313","https://openalex.org/W2945660127","https://openalex.org/W2962810718","https://openalex.org/W2963758027","https://openalex.org/W2983366375","https://openalex.org/W3045464143","https://openalex.org/W3112846629","https://openalex.org/W3144371756","https://openalex.org/W3154475157","https://openalex.org/W3174820758","https://openalex.org/W3176108421","https://openalex.org/W3211860396","https://openalex.org/W4210327919","https://openalex.org/W4210618583","https://openalex.org/W4231510805","https://openalex.org/W4281854550","https://openalex.org/W4292263718","https://openalex.org/W4312377805","https://openalex.org/W4386799811","https://openalex.org/W6639619044","https://openalex.org/W6640963894","https://openalex.org/W6690815549","https://openalex.org/W6691363302","https://openalex.org/W6726873649","https://openalex.org/W6734688555","https://openalex.org/W6751854905","https://openalex.org/W6791353385","https://openalex.org/W6803519869","https://openalex.org/W6847117418","https://openalex.org/W7011438494"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W3204019825"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"multimodal":[3],"topic":[4,76,136,197,199],"models":[5,21],"have":[6],"gained":[7],"significant":[8],"attention":[9],"in":[10,34,43,83,87,115,154,194],"various":[11],"tasks":[12],"involving":[13],"short":[14],"texts.":[15],"Despite":[16],"their":[17],"impressive":[18],"results,":[19],"most":[20],"rely":[22],"on":[23,184],"bag-of-words":[24],"assumptions":[25],"for":[26,135],"each":[27,58],"modality,":[28,90,118],"neglecting":[29],"the":[30,35,39,44,65,69,75,84,88,111,116,119,145,155,165,188,218,221],"intrinsic":[31],"word":[32,66,208],"relations":[33,42,67,72,100,120,126,209,212],"textual":[36,89],"modality":[37,60],"and":[38,68,101,127,150,160,178,201,210],"underlying":[40],"object":[41,71,211],"visual":[45,70,117,151],"modality.":[46],"To":[47,163],"address":[48],"this":[49],"limitation,":[50],"we":[51,168],"propose":[52],"a":[53,62],"novel":[54],"approach":[55,80],"that":[56,173,206],"represents":[57],"document":[59],"as":[61,96,124],"graph,":[63],"harnessing":[64],"to":[73,107,110],"guide":[74],"extraction":[77],"process.":[78],"Our":[79],"is":[81],"grounded":[82],"insight":[85],"that,":[86],"words":[91,149],"with":[92],"specific":[93],"relations,":[94,98,103,129],"such":[95,123],"co-occurrence":[97],"semantic":[99],"syntactic":[102],"are":[104],"more":[105,158],"likely":[106],"be":[108],"assigned":[109],"same":[112],"topic.":[113],"Similarly,":[114],"between":[121,148],"objects,":[122,152],"spatial":[125],"contextual":[128],"can":[130],"also":[131],"provide":[132],"valuable":[133],"information":[134],"extraction.":[137],"By":[138],"leveraging":[139],"graph-based":[140,214],"representations,":[141],"our":[142,191],"model":[143,193],"captures":[144],"inherent":[146],"associations":[147],"resulting":[153],"generation":[156],"of":[157,190,196,220],"coherent":[159],"interpretable":[161],"topics.":[162,223],"infer":[164],"model's":[166],"parameters,":[167],"develop":[169],"an":[170],"effective":[171],"algorithm":[172],"integrates":[174],"neural":[175],"variational":[176],"inference":[177],"contrastive":[179],"learning.":[180],"The":[181],"experimental":[182],"results":[183],"three":[185],"datasets":[186],"verify":[187],"effectiveness":[189],"proposed":[192],"terms":[195],"coherence,":[198],"diversity":[200],"mean":[202],"average":[203],"precision,":[204],"confirming":[205],"incorporating":[207],"through":[213],"representations":[215],"significantly":[216],"enhances":[217],"quality":[219],"extracted":[222]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
