{"id":"https://openalex.org/W2804608824","doi":"https://doi.org/10.18653/v1/w18-2314","title":"Convolutional neural networks for chemical-disease relation extraction are improved with character-based word embeddings","display_name":"Convolutional neural networks for chemical-disease relation extraction are improved with character-based word embeddings","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2804608824","doi":"https://doi.org/10.18653/v1/w18-2314","mag":"2804608824"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w18-2314","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-2314","pdf_url":"https://www.aclweb.org/anthology/W18-2314.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 BioNLP 2018 workshop","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W18-2314.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","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":true,"raw_author_name":"Dat Quoc Nguyen","raw_affiliation_strings":["School of Computing and Information Systems The University of Melbourne, Australia","University of Melbourne"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Systems The University of Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"University of Melbourne","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","University of Melbourne"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Systems The University of Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"University of Melbourne","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5063933953"],"corresponding_institution_ids":["https://openalex.org/I165779595"],"apc_list":null,"apc_paid":null,"fwci":0.8461,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.80043086,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"129","last_page":"136"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9994999766349792,"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":0.9976000189781189,"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":0.8494833707809448},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7861003875732422},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.7764748334884644},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7396204471588135},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7306522727012634},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7130379676818848},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.604401171207428},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.603114664554596},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.5938441753387451},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4543515741825104},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.33212000131607056},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.33015286922454834},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3293789029121399},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.12871283292770386},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10186219215393066},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.07154470682144165}],"concepts":[{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.8494833707809448},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7861003875732422},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.7764748334884644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7396204471588135},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7306522727012634},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7130379676818848},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.604401171207428},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.603114664554596},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.5938441753387451},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4543515741825104},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.33212000131607056},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33015286922454834},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3293789029121399},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.12871283292770386},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10186219215393066},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.07154470682144165},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.18653/v1/w18-2314","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-2314","pdf_url":"https://www.aclweb.org/anthology/W18-2314.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 BioNLP 2018 workshop","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1805.10586","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1805.10586","pdf_url":"https://arxiv.org/pdf/1805.10586","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2804608824","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1805.10586.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1805.10586","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1805.10586","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.18653/v1/w18-2314","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-2314","pdf_url":"https://www.aclweb.org/anthology/W18-2314.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 BioNLP 2018 workshop","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2804608824.pdf","grobid_xml":"https://content.openalex.org/works/W2804608824.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W46679369","https://openalex.org/W90362830","https://openalex.org/W1632114991","https://openalex.org/W2053238041","https://openalex.org/W2055032581","https://openalex.org/W2095705004","https://openalex.org/W2107598941","https://openalex.org/W2120814856","https://openalex.org/W2138627627","https://openalex.org/W2158040974","https://openalex.org/W2163303745","https://openalex.org/W2163362093","https://openalex.org/W2229639163","https://openalex.org/W2240668419","https://openalex.org/W2250861254","https://openalex.org/W2251135946","https://openalex.org/W2251622960","https://openalex.org/W2252215182","https://openalex.org/W2296283641","https://openalex.org/W2335791510","https://openalex.org/W2475245295","https://openalex.org/W2515248967","https://openalex.org/W2515462165","https://openalex.org/W2527712604","https://openalex.org/W2574454672","https://openalex.org/W2577666659","https://openalex.org/W2578456568","https://openalex.org/W2604372572","https://openalex.org/W2626778328","https://openalex.org/W2738031524","https://openalex.org/W2740114211","https://openalex.org/W2740232286","https://openalex.org/W2741956709","https://openalex.org/W2759056771","https://openalex.org/W2765242061","https://openalex.org/W2775521672","https://openalex.org/W2794309877","https://openalex.org/W2903382683","https://openalex.org/W2952436057","https://openalex.org/W2953384591","https://openalex.org/W2962784628","https://openalex.org/W2963454301","https://openalex.org/W2964090065","https://openalex.org/W2964193968","https://openalex.org/W3101763502"],"related_works":["https://openalex.org/W3155172179","https://openalex.org/W2806154504","https://openalex.org/W2913145687","https://openalex.org/W2769218485","https://openalex.org/W2198675581","https://openalex.org/W2965276554","https://openalex.org/W3087886709","https://openalex.org/W3102498271","https://openalex.org/W3084574658","https://openalex.org/W2795058418","https://openalex.org/W3180787840","https://openalex.org/W1841724727","https://openalex.org/W3200156078","https://openalex.org/W2999223283","https://openalex.org/W3037538309","https://openalex.org/W3040779069","https://openalex.org/W2776708490","https://openalex.org/W3197784004","https://openalex.org/W2893720751","https://openalex.org/W2908040686"],"abstract_inverted_index":{"We":[0,15],"investigate":[1],"the":[2,37,52],"incorporation":[3],"of":[4],"character-based":[5,53],"word":[6,27,54],"representations":[7,29,55],"into":[8],"a":[9,34],"standard":[10],"CNN-based":[11],"relation":[12],"extraction":[13],"model.":[14],"experiment":[16],"with":[17],"two":[18],"common":[19],"neural":[20,71],"architectures,":[21],"CNN":[22],"and":[23,45],"LSTM,":[24],"to":[25,69],"learn":[26],"vector":[28],"from":[30],"character":[31],"embeddings.":[32],"Through":[33],"task":[35],"on":[36,57],"BioCreative-V":[38],"CDR":[39],"corpus,":[40],"extracting":[41],"relationships":[42],"between":[43],"chemicals":[44],"diseases,":[46],"we":[47],"show":[48],"that":[49,59],"models":[50,58],"exploiting":[51],"improve":[56],"do":[60],"not":[61],"use":[62],"this":[63],"information,":[64],"obtaining":[65],"state-of-the-art":[66],"result":[67],"relative":[68],"previous":[70],"approaches.":[72]},"counts_by_year":[{"year":2021,"cited_by_count":3},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
