{"id":"https://openalex.org/W4212998232","doi":"https://doi.org/10.1145/3488560.3498475","title":"MAF: A General Matching and Alignment Framework for Multimodal Named Entity Recognition","display_name":"MAF: A General Matching and Alignment Framework for Multimodal Named Entity Recognition","publication_year":2022,"publication_date":"2022-02-11","ids":{"openalex":"https://openalex.org/W4212998232","doi":"https://doi.org/10.1145/3488560.3498475"},"language":"en","primary_location":{"id":"doi:10.1145/3488560.3498475","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498475","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","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/A5020681500","display_name":"Bo Xu","orcid":"https://orcid.org/0000-0002-2083-4307"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Xu","raw_affiliation_strings":["Donghua University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087643562","display_name":"Shizhou Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shizhou Huang","raw_affiliation_strings":["Donghua University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083750020","display_name":"Chaofeng Sha","orcid":"https://orcid.org/0009-0004-4195-0122"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaofeng Sha","raw_affiliation_strings":["Fudan University &amp; Shanghai Key Laboratory of Intelligence Processing, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University &amp; Shanghai Key Laboratory of Intelligence Processing, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107916174","display_name":"Hongya Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongya Wang","raw_affiliation_strings":["Donghua University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":106,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1215","last_page":"1223"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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":0.9995999932289124,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9990000128746033,"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/computer-science","display_name":"Computer science","score":0.8103244304656982},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5978078246116638},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5948866009712219},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.562937319278717},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5605763792991638},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5590201616287231},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5583173632621765},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5357246994972229},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5151480436325073},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4883260428905487},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4666808843612671},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4505048096179962},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42604056000709534},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3935070037841797},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33689260482788086}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8103244304656982},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5978078246116638},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5948866009712219},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.562937319278717},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5605763792991638},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5590201616287231},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5583173632621765},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5357246994972229},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5151480436325073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4883260428905487},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4666808843612671},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4505048096179962},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42604056000709534},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3935070037841797},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33689260482788086},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3488560.3498475","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498475","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1593127992","display_name":null,"funder_award_id":"2232021A-08","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1554540371","https://openalex.org/W2194775991","https://openalex.org/W2296283641","https://openalex.org/W2788647998","https://openalex.org/W2798298921","https://openalex.org/W2953072307","https://openalex.org/W2962902328","https://openalex.org/W2962982907","https://openalex.org/W3035448883","https://openalex.org/W3148395438","https://openalex.org/W3160851104","https://openalex.org/W3174525637"],"related_works":["https://openalex.org/W2366107444","https://openalex.org/W4388145910","https://openalex.org/W2381570729","https://openalex.org/W1976205134","https://openalex.org/W4248336175","https://openalex.org/W2031260042","https://openalex.org/W2185469136","https://openalex.org/W2032548952","https://openalex.org/W4301143707","https://openalex.org/W2952745240"],"abstract_inverted_index":{"In":[0],"this":[1,71,228],"paper,":[2],"we":[3,128,152,189],"study":[4],"multimodal":[5,138],"named":[6,65,139],"entity":[7,140],"recognition":[8,87,141],"in":[9,67,77,142,233],"social":[10,143],"media":[11,144],"posts.":[12,145],"Existing":[13],"works":[14],"mainly":[15],"focus":[16],"on":[17,43],"using":[18],"a":[19,44,99,116,130,154,191],"cross-modal":[20,156,193],"attention":[21],"mechanism":[22],"to":[23,62,97,102,147,160,173,197,216],"combine":[24],"text":[25,49,121,166],"representation":[26,101],"with":[27],"image":[28,53,58],"representation.":[29],"However,":[30,70],"they":[31],"still":[32],"suffer":[33],"from":[34,114],"two":[35,108,203],"weaknesses:":[36],"(1)":[37],"the":[38,57,68,81,86,93,104,112,120,149,162,171,175,186,199,202,218],"current":[39,94],"methods":[40,95],"are":[41,54],"based":[42],"strong":[45,82],"assumption":[46,72,83],"that":[47,180],"each":[48],"and":[50,56,80,122,133,167,169,213,220],"its":[51],"accompanying":[52],"matched,":[55],"can":[59,230],"be":[60,182,231],"used":[61],"help":[63],"identify":[64],"entities":[66],"text.":[69],"is":[73],"not":[74],"always":[75],"true":[76],"real":[78],"scenarios,":[79],"may":[84],"reduce":[85],"effect":[88],"of":[89,177,201,222,227],"theMNER":[90],"model;":[91],"(2)":[92],"fail":[96],"construct":[98],"consistent":[100],"bridge":[103],"semantic":[105],"gap":[106],"between":[107,119,165],"modalities,":[109],"which":[110],"prevents":[111],"model":[113],"establishing":[115],"good":[117],"connection":[118],"image.":[123],"To":[124,184],"address":[125],"these":[126],"issues,":[127],"propose":[129,153,190],"general":[131],"matching":[132,157],"alignment":[134,194],"framework":[135],"(MAF)":[136],"for":[137],"Specifically,":[146],"solve":[148,185],"first":[150],"issue,":[151,188],"novel":[155,192],"(CM)":[158],"module":[159,196],"calculate":[161],"similarity":[163],"score":[164,172],"image,":[168],"use":[170],"determine":[174],"proportion":[176],"visual":[178],"information":[179],"should":[181],"retained.":[183],"second":[187],"(CA)":[195],"make":[198],"representations":[200],"modalities":[204],"more":[205],"consistent.":[206],"We":[207],"conduct":[208],"extensive":[209],"experiments,":[210],"ablation":[211],"studies,":[212],"case":[214],"studies":[215],"demonstrate":[217],"effectiveness":[219],"efficiency":[221],"our":[223],"method.The":[224],"source":[225],"code":[226],"paper":[229],"found":[232],"https://github.com/xubodhu/MAF.":[234]},"counts_by_year":[{"year":2026,"cited_by_count":20},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":30},{"year":2023,"cited_by_count":27},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-10T00:00:00"}
