{"id":"https://openalex.org/W4391308154","doi":"https://doi.org/10.1109/smc53992.2023.10394643","title":"A Study of Chinese Medicine Entity Recognition Method by Fusing Multi-Features and Pointer Networks","display_name":"A Study of Chinese Medicine Entity Recognition Method by Fusing Multi-Features and Pointer Networks","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4391308154","doi":"https://doi.org/10.1109/smc53992.2023.10394643"},"language":"en","primary_location":{"id":"doi:10.1109/smc53992.2023.10394643","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/smc53992.2023.10394643","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5031589563","display_name":"Zihao Lv","orcid":"https://orcid.org/0009-0008-0196-7797"},"institutions":[{"id":"https://openalex.org/I16351329","display_name":"China West Normal University","ror":"https://ror.org/04s99y476","country_code":"CN","type":"education","lineage":["https://openalex.org/I16351329"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zihao Lv","raw_affiliation_strings":["Computer School of China West Normal University,Nanchong,Sichuan,China,637002"],"affiliations":[{"raw_affiliation_string":"Computer School of China West Normal University,Nanchong,Sichuan,China,637002","institution_ids":["https://openalex.org/I16351329"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111781272","display_name":"Chunlin He","orcid":"https://orcid.org/0009-0005-3669-2584"},"institutions":[{"id":"https://openalex.org/I16351329","display_name":"China West Normal University","ror":"https://ror.org/04s99y476","country_code":"CN","type":"education","lineage":["https://openalex.org/I16351329"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunlin He","raw_affiliation_strings":["Computer School of China West Normal University,Nanchong,Sichuan,China,637002"],"affiliations":[{"raw_affiliation_string":"Computer School of China West Normal University,Nanchong,Sichuan,China,637002","institution_ids":["https://openalex.org/I16351329"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078693770","display_name":"Liming Xu","orcid":"https://orcid.org/0000-0002-0671-8182"},"institutions":[{"id":"https://openalex.org/I16351329","display_name":"China West Normal University","ror":"https://ror.org/04s99y476","country_code":"CN","type":"education","lineage":["https://openalex.org/I16351329"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liming Xu","raw_affiliation_strings":["Computer School of China West Normal University,Nanchong,Sichuan,China,637002"],"affiliations":[{"raw_affiliation_string":"Computer School of China West Normal University,Nanchong,Sichuan,China,637002","institution_ids":["https://openalex.org/I16351329"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5031589563"],"corresponding_institution_ids":["https://openalex.org/I16351329"],"apc_list":null,"apc_paid":null,"fwci":0.3537,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.70219912,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"abs/1412.3555()","issue":null,"first_page":"2087","last_page":"2092"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pointer","display_name":"Pointer (user interface)","score":0.7548271417617798},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7341189384460449},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5859519243240356},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47637149691581726},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3218083381652832}],"concepts":[{"id":"https://openalex.org/C150202949","wikidata":"https://www.wikidata.org/wiki/Q107602","display_name":"Pointer (user interface)","level":2,"score":0.7548271417617798},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7341189384460449},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5859519243240356},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47637149691581726},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3218083381652832}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc53992.2023.10394643","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/smc53992.2023.10394643","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3439715140","display_name":null,"funder_award_id":"KCXTD2022-3","funder_id":"https://openalex.org/F4320324420","funder_display_name":"China West Normal University"},{"id":"https://openalex.org/G6686927789","display_name":null,"funder_award_id":"62206224","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"},{"id":"https://openalex.org/F4320324420","display_name":"China West Normal University","ror":"https://ror.org/04s99y476"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W569478347","https://openalex.org/W1924770834","https://openalex.org/W2171928131","https://openalex.org/W2640329709","https://openalex.org/W2769387903","https://openalex.org/W2807800730","https://openalex.org/W2962904552","https://openalex.org/W2965373594","https://openalex.org/W2971098335","https://openalex.org/W2997222178","https://openalex.org/W3004611733","https://openalex.org/W3011594683","https://openalex.org/W3034379414","https://openalex.org/W3035625205","https://openalex.org/W3146366485","https://openalex.org/W3167243402","https://openalex.org/W3168197293","https://openalex.org/W3174142642","https://openalex.org/W3200098776","https://openalex.org/W3213591530","https://openalex.org/W3215317537","https://openalex.org/W4245551996","https://openalex.org/W4282939402","https://openalex.org/W6766673545"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2387387477","https://openalex.org/W2394051415","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W3204019825"],"abstract_inverted_index":{"The":[0,180],"recognition":[1,53,71,75,196],"of":[2,17,27,55,65,92,99,130,145,152,168,177,198],"named":[3,56,194],"entities":[4,57],"in":[5,14,58,69,190],"Traditional":[6],"Chinese":[7,78],"medicine":[8],"(TCM)":[9],"is":[10,85],"a":[11,24],"difficult":[12],"task":[13],"the":[15,52,63,95,100,105,116,127,141,146,150,153,166,172,178,193],"field":[16],"medical":[18],"information":[19,68,98,129],"extraction,":[20],"which":[21],"often":[22],"contains":[23],"large":[25],"number":[26],"domain":[28],"nouns":[29],"and":[30,37,41,60,81,110,114,122,133,148,159,170,175],"specialized":[31],"terms":[32],"with":[33,108,192],"high":[34],"semantic":[35,67],"complexity":[36],"unclear":[38],"entity":[39,70,74,147,195],"boundaries":[40],"multiple":[42],"meanings":[43],"among":[44],"some":[45],"entities.":[46],"In":[47,155],"order":[48],"to":[49,61,87,125,139,164],"effectively":[50],"solve":[51],"problem":[54,197],"TCM,":[59],"address":[62],"phenomenon":[64],"underutilized":[66],"tasks,":[72],"an":[73],"method":[76,186],"incorporating":[77],"character":[79,89,106],"multi-features":[80],"SPAN":[82,136],"pointer":[83,137],"networks":[84],"proposed":[86],"obtain":[88,115,126],"feature":[90,112],"vectors":[91,107],"data":[93],"using":[94],"powerful":[96],"characterization":[97],"pre-training":[101],"model":[102],"BERT,":[103],"connect":[104],"lexical":[109],"radical":[111],"embeddings,":[113],"long-range":[117,131],"textual":[118],"context":[119],"through":[120],"BiGRU":[121],"Attention":[123],"layer":[124],"contextual":[128],"text,":[132],"finally":[134],"use":[135],"network":[138],"achieve":[140],"start":[142],"boundary":[143],"determination":[144],"complete":[149],"extraction":[151],"entity.":[154],"addition,":[156],"adversarial":[157],"training":[158],"focal":[160],"loss":[161],"are":[162],"added":[163],"reduce":[165],"risk":[167],"overfitting":[169],"enhance":[171],"generalization":[173],"ability":[174],"robustness":[176],"model.":[179],"final":[181],"experiments":[182],"show":[183],"that":[184],"this":[185],"has":[187],"superior":[188],"performance":[189],"dealing":[191],"TCM.":[199]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}