{"id":"https://openalex.org/W7164852017","doi":"https://doi.org/10.1145/3805622.3810756","title":"TASEN: Topic-Aware Semantic Enhancement Network for Multimodal Named Entity Recognition","display_name":"TASEN: Topic-Aware Semantic Enhancement Network for Multimodal Named Entity Recognition","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7164852017","doi":"https://doi.org/10.1145/3805622.3810756"},"language":null,"primary_location":{"id":"doi:10.1145/3805622.3810756","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810756","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3805622.3810756","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081309858","display_name":"Guohui Ding","orcid":"https://orcid.org/0000-0001-9548-7701"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]},{"id":"https://openalex.org/I42852656","display_name":"Shenyang University","ror":"https://ror.org/04ddfwm68","country_code":"CN","type":"education","lineage":["https://openalex.org/I42852656"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guohui Ding","raw_affiliation_strings":["Shenyang Aerospace Universtiy, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0001-9548-7701","affiliations":[{"raw_affiliation_string":"Shenyang Aerospace Universtiy, Shenyang, China","institution_ids":["https://openalex.org/I42852656","https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126098057","display_name":"Chufei Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chufei Wang","raw_affiliation_strings":["Shenyang Aerospace University, Shenyang, China"],"raw_orcid":"https://orcid.org/0009-0001-9898-0750","affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University, Shenyang, China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100674676","display_name":"Hongfeng Wang","orcid":"https://orcid.org/0000-0002-8954-0876"},"institutions":[{"id":"https://openalex.org/I4210094459","display_name":"Craft Group (China)","ror":"https://ror.org/00gxm5663","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210094459"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongfeng Wang","raw_affiliation_strings":["AVIC Shenyang Aircraft Industry (Group) Co., Ltd., Shenyang, China"],"raw_orcid":"https://orcid.org/0009-0009-3577-3066","affiliations":[{"raw_affiliation_string":"AVIC Shenyang Aircraft Industry (Group) Co., Ltd., Shenyang, China","institution_ids":["https://openalex.org/I4210094459"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070441614","display_name":"Oleksandr Zakovorotnyi","orcid":"https://orcid.org/0000-0003-4415-838X"},"institutions":[{"id":"https://openalex.org/I67256668","display_name":"National Technical University \"Kharkiv Polytechnic Institute\"","ror":"https://ror.org/00yp5c433","country_code":"UA","type":"education","lineage":["https://openalex.org/I67256668"]}],"countries":["UA"],"is_corresponding":false,"raw_author_name":"Zakovorotnyi Oleksandr","raw_affiliation_strings":["National Technical University Kharkiv Polytechnic Institute, Kharkiv, Ukraine"],"raw_orcid":"https://orcid.org/0000-0003-4415-838X","affiliations":[{"raw_affiliation_string":"National Technical University Kharkiv Polytechnic Institute, Kharkiv, Ukraine","institution_ids":["https://openalex.org/I67256668"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.95024215,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"672","last_page":"680"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.8618999719619751,"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":0.8618999719619751,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.023600000888109207,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.022299999371170998,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/leverage","display_name":"Leverage (statistics)","score":0.5849999785423279},{"id":"https://openalex.org/keywords/complementarity","display_name":"Complementarity (molecular biology)","score":0.5156000256538391},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5123000144958496},{"id":"https://openalex.org/keywords/entity-linking","display_name":"Entity linking","score":0.4740000069141388},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.43869999051094055},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.43160000443458557},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.41190001368522644},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"Named-entity recognition","score":0.4023999869823456}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8109999895095825},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5849999785423279},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5595999956130981},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.529699981212616},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.5156000256538391},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5123000144958496},{"id":"https://openalex.org/C96711827","wikidata":"https://www.wikidata.org/wiki/Q17012245","display_name":"Entity linking","level":3,"score":0.4740000069141388},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.43869999051094055},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.436599999666214},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.43160000443458557},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.41190001368522644},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.4023999869823456},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.3813000023365021},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.32739999890327454},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.31040000915527344},{"id":"https://openalex.org/C202708506","wikidata":"https://www.wikidata.org/wiki/Q7449050","display_name":"Semantic compression","level":5,"score":0.3098999857902527},{"id":"https://openalex.org/C85407183","wikidata":"https://www.wikidata.org/wiki/Q1045785","display_name":"Semantic network","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.25519999861717224},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.2540000081062317},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3805622.3810756","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810756","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3805622.3810756","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810756","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W40976687","https://openalex.org/W2020278455","https://openalex.org/W2070808142","https://openalex.org/W2113855231","https://openalex.org/W2122678284","https://openalex.org/W2147152072","https://openalex.org/W2296283641","https://openalex.org/W2558405088","https://openalex.org/W2788647998","https://openalex.org/W2798298921","https://openalex.org/W2962982907","https://openalex.org/W2963658877","https://openalex.org/W3003940182","https://openalex.org/W3011594683","https://openalex.org/W3042602466","https://openalex.org/W3127151332","https://openalex.org/W3176858586","https://openalex.org/W3199057778","https://openalex.org/W4212998232","https://openalex.org/W4229011615","https://openalex.org/W4287854428","https://openalex.org/W4304091743","https://openalex.org/W4313327571","https://openalex.org/W4321488427","https://openalex.org/W4382466550","https://openalex.org/W4385573247","https://openalex.org/W4387848810","https://openalex.org/W4387968507","https://openalex.org/W4399418591","https://openalex.org/W7131895871"],"related_works":[],"abstract_inverted_index":{"Multimodal":[0,161],"Named":[1],"Entity":[2],"Recognition":[3],"(MNER)":[4],"aims":[5],"to":[6,10,102,133,167],"leverage":[7],"visual":[8],"information":[9,43,61,137],"assist":[11],"text-based":[12],"entity":[13,63],"recognition.":[14],"However,":[15],"most":[16],"existing":[17],"studies":[18],"on":[19,22,186],"MNER":[20,93],"focus":[21],"modeling":[23],"individual":[24],"image\u2013text":[25],"pairs,":[26],"overlooking":[27],"the":[28,34,38,54,69,77,95,150,176,187],"semantic":[29,109],"complementarity":[30],"across":[31],"samples":[32],"within":[33],"same":[35,55],"topic":[36,42,56,116,136,155],"and":[37,51,68,120,124,141,192],"guiding":[39],"role":[40],"of":[41,72,98,106,153,178],"in":[44,181],"social":[45],"media":[46],"data.":[47],"In":[48,157],"practice,":[49],"texts":[50,73],"images":[52],"under":[53],"can":[57,74],"provide":[58],"richer":[59],"complementary":[60],"for":[62],"recognition":[64,78,177],"through":[65],"shared":[66],"context,":[67],"topic-level":[70],"semantics":[71],"further":[75],"guide":[76],"process.":[79],"To":[80],"this":[81],"end,":[82],"we":[83],"propose":[84],"a":[85,103,127,159],"Topic-Aware":[86],"Semantic":[87],"Enhancement":[88,162],"Network":[89],"(TASEN),":[90],"which":[91],"transforms":[92],"from":[94,172],"traditional":[96],"paradigm":[97],"single-sample":[99],"multimodal":[100,170],"alignment":[101],"new":[104],"perspective":[105],"cross-sample":[107,169],"topic-aware":[108],"enhancement.":[110],"Specifically,":[111],"TASEN":[112,196],"first":[113],"performs":[114],"hierarchical":[115,135],"clustering":[117],"using":[118],"BERTopic":[119],"selects":[121],"same-topic":[122,173],"neighbors,":[123,174],"then":[125],"employs":[126],"Hyperbolic":[128],"Topic":[129],"Fusion":[130],"(HTF)":[131],"module":[132,164],"map":[134],"into":[138],"hyperbolic":[139],"space":[140],"geometrically":[142],"fuse":[143],"it":[144],"with":[145],"textual":[146],"representations,":[147],"thereby":[148],"enhancing":[149],"model\u2019s":[151],"awareness":[152],"global":[154],"hierarchies.":[156],"addition,":[158],"Cross-Sample":[160],"(CSME)":[163],"is":[165],"introduced":[166],"integrate":[168],"representations":[171],"strengthening":[175],"hard-to-identify":[179],"entities":[180],"short":[182],"texts.":[183],"Extensive":[184],"experiments":[185],"popular":[188],"public":[189],"datasets":[190],"Twitter-2015":[191],"Twitter-2017":[193],"demonstrate":[194],"that":[195],"significantly":[197],"outperforms":[198],"strong":[199],"baselines.":[200]},"counts_by_year":[],"updated_date":"2026-06-16T07:37:23.134862","created_date":"2026-06-16T00:00:00"}