{"id":"https://openalex.org/W2888597024","doi":"https://doi.org/10.18653/v1/w18-5605","title":"Comparing CNN and LSTM character-level embeddings in BiLSTM-CRF models for chemical and disease named entity recognition","display_name":"Comparing CNN and LSTM character-level embeddings in BiLSTM-CRF models for chemical and disease named entity recognition","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2888597024","doi":"https://doi.org/10.18653/v1/w18-5605","mag":"2888597024"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w18-5605","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-5605","pdf_url":"https://www.aclweb.org/anthology/W18-5605.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Ninth International Workshop on Health Text Mining and Information Analysis","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W18-5605.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011798464","display_name":"Zenan Zhai","orcid":"https://orcid.org/0000-0003-1391-6950"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Zenan Zhai","raw_affiliation_strings":["School of Computing and Information Systems The University of Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Systems The University of Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063933953","display_name":"Dat Quoc Nguyen","orcid":"https://orcid.org/0000-0001-8214-2878"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Dat Quoc Nguyen","raw_affiliation_strings":["School of Computing and Information Systems The University of Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Systems The University of Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067214173","display_name":"Karin Verspoor","orcid":"https://orcid.org/0000-0002-8661-1544"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Karin Verspoor","raw_affiliation_strings":["School of Computing and Information Systems The University of Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Systems The University of Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5011798464"],"corresponding_institution_ids":["https://openalex.org/I165779595"],"apc_list":null,"apc_paid":null,"fwci":3.7461,"has_fulltext":true,"cited_by_count":38,"citation_normalized_percentile":{"value":0.94572291,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9951000213623047,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.8246070742607117},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.793941855430603},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.7900534868240356},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7059303522109985},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6034948825836182},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"Named-entity recognition","score":0.5841740965843201},{"id":"https://openalex.org/keywords/conjunction","display_name":"Conjunction (astronomy)","score":0.4689091444015503},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.46405187249183655},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.0876883864402771},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07839018106460571},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.05318295955657959}],"concepts":[{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.8246070742607117},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.793941855430603},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.7900534868240356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7059303522109985},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6034948825836182},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.5841740965843201},{"id":"https://openalex.org/C59656382","wikidata":"https://www.wikidata.org/wiki/Q191536","display_name":"Conjunction (astronomy)","level":2,"score":0.4689091444015503},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.46405187249183655},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0876883864402771},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07839018106460571},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.05318295955657959},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/w18-5605","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-5605","pdf_url":"https://www.aclweb.org/anthology/W18-5605.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Ninth International Workshop on Health Text Mining and Information Analysis","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/w18-5605","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-5605","pdf_url":"https://www.aclweb.org/anthology/W18-5605.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Ninth International Workshop on Health Text Mining and Information Analysis","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2888597024.pdf","grobid_xml":"https://content.openalex.org/works/W2888597024.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W192665053","https://openalex.org/W1940872118","https://openalex.org/W2064675550","https://openalex.org/W2095596879","https://openalex.org/W2121244856","https://openalex.org/W2131774270","https://openalex.org/W2142016317","https://openalex.org/W2144578941","https://openalex.org/W2147800946","https://openalex.org/W2153579005","https://openalex.org/W2163303745","https://openalex.org/W2169491861","https://openalex.org/W2296283641","https://openalex.org/W2346452181","https://openalex.org/W2414378847","https://openalex.org/W2553397501","https://openalex.org/W2734608416","https://openalex.org/W2738180183","https://openalex.org/W2766140847","https://openalex.org/W2769387903","https://openalex.org/W2952087486","https://openalex.org/W2952436057","https://openalex.org/W2962902328","https://openalex.org/W2963940534","https://openalex.org/W4294170691"],"related_works":["https://openalex.org/W1573992054","https://openalex.org/W1599690842","https://openalex.org/W2753053412","https://openalex.org/W2665157442","https://openalex.org/W3108840034","https://openalex.org/W4388169484","https://openalex.org/W2363259562","https://openalex.org/W3036937347","https://openalex.org/W3149224203","https://openalex.org/W2914339338"],"abstract_inverted_index":{"We":[0],"compare":[1],"the":[2,27,34,46,55,76,84],"use":[3,35],"of":[4,36,39],"LSTM-based":[5,77],"and":[6,17],"CNN-based":[7,58],"character-level":[8,40,59],"word":[9,41,60,79],"embeddings":[10,42,61,80],"in":[11,43],"BiLSTM-CRF":[12,47],"models":[13,48,56,72],"to":[14,50],"approach":[15],"chemical":[16],"disease":[18],"named":[19],"entity":[20],"recognition":[21],"(NER)":[22],"tasks.":[23],"Empirical":[24],"results":[25],"over":[26,70],"BioCreative":[28],"V":[29],"CDR":[30],"corpus":[31],"show":[32],"that":[33],"either":[37],"type":[38],"conjunction":[44],"with":[45],"leads":[49],"comparable":[51],"state-of-theart":[52],"performance.":[53],"However,":[54],"using":[57],"have":[62],"a":[63],"computational":[64],"performance":[65],"advantage,":[66],"increasing":[67],"training":[68,86],"time":[69],"word-based":[71],"by":[73],"25%":[74],"while":[75],"characterlevel":[78],"more":[81],"than":[82],"double":[83],"required":[85],"time.":[87]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
