{"id":"https://openalex.org/W4220738390","doi":"https://doi.org/10.1145/3522736","title":"AIP: A Named Entity Recognition Method Combining Glyphs and Sounds","display_name":"AIP: A Named Entity Recognition Method Combining Glyphs and Sounds","publication_year":2022,"publication_date":"2022-03-15","ids":{"openalex":"https://openalex.org/W4220738390","doi":"https://doi.org/10.1145/3522736"},"language":"en","primary_location":{"id":"doi:10.1145/3522736","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3522736","pdf_url":null,"source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","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/A5100461634","display_name":"Bo Liu","orcid":"https://orcid.org/0000-0002-2393-117X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]},{"id":"https://openalex.org/I51158804","display_name":"Massey University","ror":"https://ror.org/052czxv31","country_code":"NZ","type":"education","lineage":["https://openalex.org/I51158804"]}],"countries":["CN","NZ"],"is_corresponding":false,"raw_author_name":"Bo Liu","raw_affiliation_strings":["Faculty of Information Technology, Beijing University of Technology, Beijing, China and School of Mathematical and Computational Sciences, Massey University, Palmerston North, New Zealand"],"raw_orcid":"https://orcid.org/0000-0002-2393-117X","affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Beijing University of Technology, Beijing, China and School of Mathematical and Computational Sciences, Massey University, Palmerston North, New Zealand","institution_ids":["https://openalex.org/I51158804","https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067564709","display_name":"Zhuo Su","orcid":"https://orcid.org/0000-0003-2571-9436"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuo Su","raw_affiliation_strings":["Faculty of Information Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2571-9436","affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005828574","display_name":"Guangzhi Qu","orcid":"https://orcid.org/0000-0003-4047-9514"},"institutions":[{"id":"https://openalex.org/I177721651","display_name":"Oakland University","ror":"https://ror.org/01ythxj32","country_code":"US","type":"education","lineage":["https://openalex.org/I177721651"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guangzhi Qu","raw_affiliation_strings":["Computer Science and Engineering Department, Oakland University, Rochester, MI, USA"],"raw_orcid":"https://orcid.org/0000-0003-4047-9514","affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, Oakland University, Rochester, MI, USA","institution_ids":["https://openalex.org/I177721651"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4162,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66711635,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"21","issue":"6","first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9983999729156494,"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":0.9952999949455261,"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/glyph","display_name":"Glyph (data visualization)","score":0.9349435567855835},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7747431993484497},{"id":"https://openalex.org/keywords/pinyin","display_name":"Pinyin","score":0.6247493028640747},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.604119062423706},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5848740339279175},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5754246711730957},{"id":"https://openalex.org/keywords/chinese-characters","display_name":"Chinese characters","score":0.5347676873207092},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5141358971595764},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.5092133283615112},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5017976760864258},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4637518525123596},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4189998507499695},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4141005873680115},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4013587236404419},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.2004147469997406},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.12112745642662048},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0768410861492157}],"concepts":[{"id":"https://openalex.org/C142816647","wikidata":"https://www.wikidata.org/wiki/Q5573018","display_name":"Glyph (data visualization)","level":3,"score":0.9349435567855835},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7747431993484497},{"id":"https://openalex.org/C2781095461","wikidata":"https://www.wikidata.org/wiki/Q42222","display_name":"Pinyin","level":3,"score":0.6247493028640747},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.604119062423706},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5848740339279175},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5754246711730957},{"id":"https://openalex.org/C2781051154","wikidata":"https://www.wikidata.org/wiki/Q8201","display_name":"Chinese characters","level":2,"score":0.5347676873207092},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5141358971595764},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.5092133283615112},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5017976760864258},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4637518525123596},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4189998507499695},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4141005873680115},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4013587236404419},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2004147469997406},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.12112745642662048},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0768410861492157},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3522736","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3522736","pdf_url":null,"source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.699999988079071}],"awards":[{"id":"https://openalex.org/G4355366799","display_name":null,"funder_award_id":"62076015","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1594229598","https://openalex.org/W1607093392","https://openalex.org/W1912843035","https://openalex.org/W2064675550","https://openalex.org/W2107878631","https://openalex.org/W2118822954","https://openalex.org/W2136038431","https://openalex.org/W2251131401","https://openalex.org/W2531638282","https://openalex.org/W2559281960","https://openalex.org/W2796831711","https://openalex.org/W2910655080","https://openalex.org/W2962902328","https://openalex.org/W2962904552","https://openalex.org/W2963446712","https://openalex.org/W2980708516","https://openalex.org/W2982238957","https://openalex.org/W3002784191","https://openalex.org/W3104774463","https://openalex.org/W3140899690","https://openalex.org/W3174396451","https://openalex.org/W6679881089"],"related_works":["https://openalex.org/W4385493412","https://openalex.org/W3159297355","https://openalex.org/W1575804004","https://openalex.org/W2386864954","https://openalex.org/W380382270","https://openalex.org/W1788792945","https://openalex.org/W2384047089","https://openalex.org/W4381616474","https://openalex.org/W2101906057","https://openalex.org/W2962951088"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"a":[3,31],"large":[4],"number":[5],"of":[6,16,46,59,81,129,137],"Chinese":[7,47,60,94,147],"electronic":[8,27],"texts":[9,28],"have":[10,50],"been":[11],"produced":[12],"in":[13,19,25,161],"the":[14,43,57,116,127,130,135,138,158,173,180,191],"process":[15],"information":[17],"construction":[18],"various":[20],"fields.":[21],"Identifying":[22],"specific":[23,162],"entities":[24],"these":[26],"has":[29],"become":[30],"major":[32],"research":[33,37],"focus.":[34],"Most":[35],"existing":[36],"methods":[38,77],"use":[39],"radicals":[40],"to":[41,125],"extract":[42],"glyph":[44,65,100],"features":[45,58],"characters":[48,61,95],"but":[49],"seen":[51],"its":[52],"limitation.":[53],"This":[54,132],"paper":[55,133],"extracts":[56],"from":[62],"three":[63],"aspects:":[64],"features,":[66,68,71],"phonetic":[67,111],"and":[69,72,108,114,141,157,186],"character":[70,122],"improves":[73],"conventional":[74],"feature":[75,101,112,123],"extraction":[76,124],"for":[78,99,110,121],"each":[79],"kind":[80],"feature.":[82],"A":[83,117],"new":[84],"named":[85,148],"entity":[86,149],"recognition":[87,150],"method":[88],"(AIP)":[89],"is":[90],"proposed":[91],"by":[92],"transforming":[93],"into":[96,105],"corresponding":[97],"images":[98],"extraction,":[102,113],"dividing":[103],"pinyin":[104],"initials,":[106],"vowels,":[107],"tones":[109],"fine-tuning":[115],"Lite":[118],"Bert":[119],"model":[120,140],"improve":[126],"performance":[128,136],"model.":[131],"compares":[134],"AIP":[139,168],"mainstream":[142],"neural":[143],"network":[144],"models":[145],"on":[146,152,179],"tasks":[151],"commonly":[153],"used":[154],"data":[155,159,182],"sets":[156,160,183],"domains.":[163],"The":[164,176],"results":[165,171],"showed":[166],"that":[167],"achieved":[169],"better":[170],"than":[172],"related":[174],"work.":[175],"F1":[177],"values":[178],"two":[181],"are":[184],"94.4%":[185],"80.5%,":[187],"respectively,":[188],"which":[189],"validates":[190],"model's":[192],"versatility.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
