{"id":"https://openalex.org/W4402351665","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650549","title":"FilterIE: A Joint multimodel information extraction model under two-stage visual data filtering","display_name":"FilterIE: A Joint multimodel information extraction model under two-stage visual data filtering","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402351665","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650549"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650549","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5041414070","display_name":"Yihan Zhao","orcid":"https://orcid.org/0000-0001-6951-4809"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yihan Zhao","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Information and Software Engineering,Chengdu,P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Information and Software Engineering,Chengdu,P.R. China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101705358","display_name":"Jun Cheng","orcid":"https://orcid.org/0000-0002-3131-3275"},"institutions":[{"id":"https://openalex.org/I4210093653","display_name":"Midea Group (China)","ror":"https://ror.org/006fm2278","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210093653"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Cheng","raw_affiliation_strings":["Midea Building Technology, Midea Group (Shanghai) Co., Ltd,Shanghai,P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Midea Building Technology, Midea Group (Shanghai) Co., Ltd,Shanghai,P.R. China","institution_ids":["https://openalex.org/I4210093653"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083640009","display_name":"Tao Meng","orcid":"https://orcid.org/0000-0002-4355-990X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I4210131342","display_name":"Yibin University","ror":"https://ror.org/03w8m2977","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131342"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Meng","raw_affiliation_strings":["YiBin Park of UESTC,Chengdu,P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"YiBin Park of UESTC,Chengdu,P.R. China","institution_ids":["https://openalex.org/I150229711","https://openalex.org/I4210131342"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082239883","display_name":"Xiaohua Wu","orcid":"https://orcid.org/0000-0002-3492-1540"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohua Wu","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Information and Software Engineering,Chengdu,P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Information and Software Engineering,Chengdu,P.R. China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":0.16587419,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9984999895095825,"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/computer-science","display_name":"Computer science","score":0.7545956373214722},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.715040922164917},{"id":"https://openalex.org/keywords/stage","display_name":"Stage (stratigraphy)","score":0.6358497738838196},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.5575039386749268},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5526330471038818},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4633021950721741},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.42739999294281006},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3813374638557434},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35285764932632446},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33449411392211914},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09017786383628845},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08922362327575684},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.05831962823867798}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7545956373214722},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.715040922164917},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.6358497738838196},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5575039386749268},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5526330471038818},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4633021950721741},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.42739999294281006},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3813374638557434},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35285764932632446},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33449411392211914},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09017786383628845},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08922362327575684},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.05831962823867798},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650549","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":30,"referenced_works":["https://openalex.org/W1490960179","https://openalex.org/W2106277773","https://openalex.org/W2525579820","https://openalex.org/W2526174222","https://openalex.org/W2618530766","https://openalex.org/W2788647998","https://openalex.org/W2798298921","https://openalex.org/W2962982907","https://openalex.org/W2963341956","https://openalex.org/W2964022985","https://openalex.org/W2987734933","https://openalex.org/W3035448883","https://openalex.org/W3126792443","https://openalex.org/W3127151332","https://openalex.org/W3184735396","https://openalex.org/W3207972321","https://openalex.org/W4237040408","https://openalex.org/W4287887264","https://openalex.org/W4385245566","https://openalex.org/W4385573478","https://openalex.org/W4392180651","https://openalex.org/W6631190155","https://openalex.org/W6691927857","https://openalex.org/W6697154816","https://openalex.org/W6715678573","https://openalex.org/W6739901393","https://openalex.org/W6767505970","https://openalex.org/W6797632053","https://openalex.org/W6840449446","https://openalex.org/W6846859655"],"related_works":["https://openalex.org/W2329386257","https://openalex.org/W2503350049","https://openalex.org/W2397616145","https://openalex.org/W2397320258","https://openalex.org/W1996130883","https://openalex.org/W2748574964","https://openalex.org/W4324058133","https://openalex.org/W648618910","https://openalex.org/W4393624937","https://openalex.org/W4296658948"],"abstract_inverted_index":{"Multimodal":[0],"information":[1,45,69,78,90,110,137,143,183],"extraction":[2,46,70,138,144,184],"has":[3],"garnered":[4],"increasing":[5],"attention":[6],"in":[7,31,55,100,171,182],"the":[8,19,26,35,41,53,56,93,132,135,141,153,179],"domain":[9],"of":[10,21,28,43,58,96,103,134,155],"natural":[11],"language":[12],"processing.":[13],"However,":[14],"current":[15],"approaches":[16],"largely":[17],"overestimate":[18],"role":[20],"visual":[22,32,77,89,104,109,121],"information,":[23],"thereby":[24],"neglecting":[25],"impact":[27],"noise":[29],"contained":[30],"data":[33],"on":[34,92],"task.":[36],"It":[37],"was":[38],"observed":[39],"that":[40,73],"accuracy":[42],"multimodal":[44,68,97,142],"models":[47],"does":[48],"not":[49],"always":[50],"improve":[51],"with":[52,140],"increase":[54],"amount":[57],"information.":[59,105],"To":[60],"tackle":[61],"these":[62],"issues,":[63],"we":[64,82],"introduce":[65],"a":[66,75,84,101,126],"joint":[67,127],"model":[71,128,139,145,181],"(FliterIE)":[72],"incorporates":[74],"two-stage":[76,85],"filtering":[79,86],"process.":[80],"Specifically,":[81],"implement":[83],"process":[87],"for":[88],"based":[91],"matching":[94,148],"degree":[95],"data,":[98],"resulting":[99],"collection":[102,107],"This":[106],"encompasses":[108],"at":[111],"both":[112],"holistic":[113],"and":[114,165,175],"object-level":[115],"granularities,":[116],"aiming":[117],"to":[118,130,178],"obtain":[119],"valuable":[120],"representations.":[122],"We":[123,167],"further":[124],"propose":[125],"strategy":[129],"combine":[131],"results":[133],"unimodal":[136],"by":[146],"dynamically":[147],"weights.":[149],"Our":[150],"experiments":[151],"validate":[152],"effectiveness":[154],"our":[156],"approach":[157],"across":[158],"three":[159],"widely":[160],"used":[161],"datasets:":[162],"Twitter-2015,":[163],"Twitter-2017,":[164],"MNRE.":[166],"achieve":[168],"state-of-the-art":[169,180],"performance":[170,177],"named":[172],"entity":[173],"recognition":[174],"comparable":[176],"tasks.":[185]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}