{"id":"https://openalex.org/W4403577409","doi":"https://doi.org/10.1145/3627673.3679706","title":"ALDF: An Adaptive Logical Decision Framework for Multimodal Named Entity Recognition","display_name":"ALDF: An Adaptive Logical Decision Framework for Multimodal Named Entity Recognition","publication_year":2024,"publication_date":"2024-10-20","ids":{"openalex":"https://openalex.org/W4403577409","doi":"https://doi.org/10.1145/3627673.3679706"},"language":"en","primary_location":{"id":"doi:10.1145/3627673.3679706","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627673.3679706","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","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/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"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guohui Ding","raw_affiliation_strings":["Shenyang Aerospace University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University, Shenyang, China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102179262","display_name":"Tianhao Jiang","orcid":"https://orcid.org/0009-0003-9413-4703"},"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":"Tianhao Jiang","raw_affiliation_strings":["Shenyang Aerospace University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University, Shenyang, China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032749574","display_name":"Rui Zhou","orcid":"https://orcid.org/0000-0001-6807-4362"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Rui Zhou","raw_affiliation_strings":["Swinburne University of Technology, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Swinburne University of Technology, Melbourne, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021552476","display_name":"Qian Gao","orcid":"https://orcid.org/0000-0002-0239-8708"},"institutions":[{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Gao","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences) &amp; Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center) &amp; Shandong Engineering Research Center of Big Data Applied Technology, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences) &amp; Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center) &amp; Shandong Engineering Research Center of Big Data Applied Technology, Jinan, China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5081309858"],"corresponding_institution_ids":["https://openalex.org/I125904092"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16304305,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"436","last_page":"445"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9991999864578247,"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/T11719","display_name":"Data Quality and Management","score":0.9657999873161316,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7882220149040222},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.489702969789505},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4570605158805847}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7882220149040222},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.489702969789505},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4570605158805847}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3627673.3679706","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627673.3679706","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W33891176","https://openalex.org/W1548890676","https://openalex.org/W2058687476","https://openalex.org/W2149129640","https://openalex.org/W2194775991","https://openalex.org/W2788647998","https://openalex.org/W2798298921","https://openalex.org/W3003940182","https://openalex.org/W3035448883","https://openalex.org/W3047144459","https://openalex.org/W3092692431","https://openalex.org/W3117216739","https://openalex.org/W3123194504","https://openalex.org/W3127151332","https://openalex.org/W3148395438","https://openalex.org/W3176858586","https://openalex.org/W4212998232","https://openalex.org/W4226372634","https://openalex.org/W4293518017","https://openalex.org/W4304015092","https://openalex.org/W4304091743","https://openalex.org/W4321488427","https://openalex.org/W4362453453","https://openalex.org/W4382317693","https://openalex.org/W4382466550","https://openalex.org/W4385573247","https://openalex.org/W6819083493"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Multimodal":[0],"Named":[1],"Entity":[2],"Recognition":[3],"(MNER)":[4],"aims":[5],"to":[6,16,65,100,131,163],"achieve":[7],"more":[8,109],"accurate":[9],"entity":[10],"recognition":[11,150],"by":[12],"incorporating":[13,56,153],"image":[14,57,74,102,115,144,154],"information":[15,62,75,94,145,188,196],"assist":[17],"text,":[18],"which":[19],"is":[20,63,76],"particularly":[21],"significant":[22],"on":[23,110,173,209],"social":[24],"media":[25],"platforms.":[26],"Current":[27],"research":[28],"disproportionately":[29],"emphasizes":[30],"enhancing":[31,169],"text":[32,51],"with":[33],"images,":[34],"overlooking":[35],"that":[36,126,184,203],"the":[37,40,68,71,90,149,158,165,170],"core":[38],"of":[39,73,88,92],"NER":[41,69,96],"task":[42],"remains":[43],"textual.":[44],"The":[45],"modal":[46],"differences":[47],"between":[48,198],"images":[49],"and":[50,107,136,194],"inevitably":[52],"introduces":[53],"noise":[54],"when":[55,60,113],"information.":[58,116],"Therefore,":[59],"textual":[61,93],"sufficient":[64],"independently":[66],"complete":[67],"task,":[70],"introduction":[72],"unnecessary.":[77],"This":[78],"paper":[79],"proposes":[80],"an":[81,128],"Adaptive":[82],"Logical":[83],"Decision":[84],"Framework":[85],"(ALDF)":[86],"capable":[87],"determining":[89],"sufficiency":[91],"in":[95,148,189],"tasks,":[97],"deciding":[98,142],"whether":[99,143],"introduce":[101],"information,":[103,155],"avoiding":[104],"unnecessary":[105],"noise,":[106],"focusing":[108],"information-scarce":[111,174],"entities":[112],"introducing":[114],"Specifically,":[117],"we":[118,156,177],"designed":[119],"a":[120,179],"Logic":[121],"Reasoning":[122],"Neural":[123],"Network":[124],"(LRNN)":[125],"uses":[127],"evidence-theory-based":[129],"method":[130,183],"simulate":[132],"human":[133],"decision-making":[134],"logic":[135],"generate":[137],"decision":[138,160,187],"support":[139,161],"degrees":[140,162],"for":[141],"should":[146],"participate":[147],"task.":[151],"When":[152],"utilize":[157],"generated":[159],"guide":[164],"multi-head":[166],"self-attention":[167],"mechanism,":[168],"model's":[171],"focus":[172],"entities.":[175],"Additionally,":[176],"employ":[178],"modality-aware":[180],"progressive":[181],"training":[182,193],"can":[185],"use":[186],"real-time":[190],"during":[191],"multimodal":[192],"reduce":[195],"redundancy":[197],"modalities.":[199],"Extensive":[200],"experiments":[201],"demonstrate":[202],"our":[204],"model":[205],"achieves":[206],"state-of-the-art":[207],"performance":[208],"popular":[210],"public":[211],"datasets.":[212]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}
