{"id":"https://openalex.org/W3034407567","doi":"https://doi.org/10.1145/3397271.3401328","title":"Improving Neural Chinese Word Segmentation with Lexicon-enhanced Adaptive Attention","display_name":"Improving Neural Chinese Word Segmentation with Lexicon-enhanced Adaptive Attention","publication_year":2020,"publication_date":"2020-07-25","ids":{"openalex":"https://openalex.org/W3034407567","doi":"https://doi.org/10.1145/3397271.3401328","mag":"3034407567"},"language":"en","primary_location":{"id":"doi:10.1145/3397271.3401328","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397271.3401328","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval","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/A5101594431","display_name":"Xiaoyan Zhao","orcid":"https://orcid.org/0000-0001-6001-1260"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoyan Zhao","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054067088","display_name":"Min Yang","orcid":"https://orcid.org/0000-0003-3814-2728"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Yang","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010974487","display_name":"Qiang Qu","orcid":"https://orcid.org/0000-0001-5814-8460"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Qu","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100714902","display_name":"Yang Sun","orcid":"https://orcid.org/0000-0002-8661-100X"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Sun","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101594431"],"corresponding_institution_ids":["https://openalex.org/I4210145761"],"apc_list":null,"apc_paid":null,"fwci":0.6628,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.75456631,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1953","last_page":"1956"},"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":0.9998999834060669,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9921000003814697,"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/lexicon","display_name":"Lexicon","score":0.8793830871582031},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8248863220214844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6928285360336304},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.633194088935852},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.622565746307373},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5903788805007935},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.49105143547058105},{"id":"https://openalex.org/keywords/text-segmentation","display_name":"Text segmentation","score":0.4557982087135315},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.45091161131858826},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42942798137664795},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.10120081901550293}],"concepts":[{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.8793830871582031},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8248863220214844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6928285360336304},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.633194088935852},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.622565746307373},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5903788805007935},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.49105143547058105},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.4557982087135315},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.45091161131858826},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42942798137664795},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.10120081901550293},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3397271.3401328","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397271.3401328","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7799999713897705,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2516334389","https://openalex.org/W2626778328","https://openalex.org/W2757350179","https://openalex.org/W2788824299","https://openalex.org/W2804552794","https://openalex.org/W2808482853","https://openalex.org/W2911295364","https://openalex.org/W3134412439"],"related_works":["https://openalex.org/W3136209078","https://openalex.org/W4392255232","https://openalex.org/W2978383222","https://openalex.org/W2172629291","https://openalex.org/W2380773642","https://openalex.org/W2384559435","https://openalex.org/W2337707338","https://openalex.org/W2393940967","https://openalex.org/W2785359773","https://openalex.org/W2159591557"],"abstract_inverted_index":{"Chinese":[0],"word":[1,99],"segmentation":[2],"(CWS)":[3],"is":[4,111],"an":[5,78],"important":[6],"research":[7],"topic":[8],"in":[9],"information":[10,100,103],"retrieval":[11],"(IR)":[12],"and":[13,117],"natural":[14],"language":[15],"processing":[16],"(NLP).":[17],"Significant":[18],"progresses":[19],"have":[20],"been":[21],"made":[22],"by":[23],"deep":[24,32],"neural":[25],"networks":[26],"with":[27,38,69,101],"context":[28,102],"features.":[29],"However,":[30],"these":[31],"models":[33],"may":[34],"fail":[35],"to":[36,67,82,94,104],"deal":[37,68],"rare":[39,71],"or":[40,72],"ambiguous":[41,73],"words,":[42],"thus":[43],"limit":[44],"the":[45,70,84,97,106,118,128],"overall":[46],"CWS":[47],"performance.":[48],"In":[49,87],"this":[50],"paper,":[51],"we":[52,76,89],"propose":[53,90],"a":[54,91],"lexicon-enhanced":[55],"adaptive":[56,79],"attention":[57,80],"network":[58],"(LAAN),":[59],"which":[60],"takes":[61],"full":[62],"advantage":[63],"of":[64,108],"external":[65],"lexicons":[66],"words.":[74],"Specifically,":[75],"devise":[77],"mechanism":[81],"learn":[83],"lexicon-aware":[85],"representation.":[86],"addition,":[88],"fusion":[92],"gate":[93],"effectively":[95],"integrate":[96],"additional":[98],"improve":[105],"performance":[107],"CWS.":[109],"LAAN":[110,123],"evaluated":[112],"on":[113],"four":[114],"benchmark":[115],"datasets,":[116],"experimental":[119],"results":[120],"demonstrate":[121],"that":[122],"has":[124],"robust":[125],"superiority":[126],"over":[127],"compared":[129],"methods.":[130]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}