{"id":"https://openalex.org/W3215989202","doi":"https://doi.org/10.1145/3487027.3487035","title":"Drug-drug interaction extraction from biomedical texts based on multi-attention mechanism","display_name":"Drug-drug interaction extraction from biomedical texts based on multi-attention mechanism","publication_year":2021,"publication_date":"2021-09-11","ids":{"openalex":"https://openalex.org/W3215989202","doi":"https://doi.org/10.1145/3487027.3487035","mag":"3215989202"},"language":"en","primary_location":{"id":"doi:10.1145/3487027.3487035","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3487027.3487035","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 8th International Conference on Bioinformatics Research and Applications","raw_type":"proceedings-article"},"type":"conference-paper","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/A5054335730","display_name":"Chengkun Wu","orcid":"https://orcid.org/0000-0002-9688-5311"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengkun Wu","raw_affiliation_strings":["College of Computer, National University of Defense Technology, China and State Key Laboratory of High-Performance Computing, National University of Defense Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, China and State Key Laboratory of High-Performance Computing, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100392089","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-8180-2886"},"institutions":[{"id":"https://openalex.org/I4210165734","display_name":"National Supercomputing Center of Tianjin","ror":"https://ror.org/05tngxm14","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210165734"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["National Supercomputer Center in Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Supercomputer Center in Tianjin, China","institution_ids":["https://openalex.org/I4210165734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102983308","display_name":"Xi Yang","orcid":"https://orcid.org/0000-0002-7418-5357"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Yang","raw_affiliation_strings":["College of Computer, National University of Defense Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101044975","display_name":"Canqun Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Canqun Yang","raw_affiliation_strings":["College of Computer, National University of Defense Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"4","issue":null,"first_page":"49","last_page":"55"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9830999970436096,"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/T10028","display_name":"Topic Modeling","score":0.9664000272750854,"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/drug","display_name":"Drug","score":0.7249484658241272},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.6428627967834473},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6219093799591064},{"id":"https://openalex.org/keywords/pharmacology","display_name":"Pharmacology","score":0.20228204131126404},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.16634449362754822},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06922805309295654}],"concepts":[{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.7249484658241272},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.6428627967834473},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6219093799591064},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.20228204131126404},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.16634449362754822},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06922805309295654},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3487027.3487035","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3487027.3487035","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 8th International Conference on Bioinformatics Research and Applications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W31959178","https://openalex.org/W1558781751","https://openalex.org/W2005568709","https://openalex.org/W2047731840","https://openalex.org/W2067704478","https://openalex.org/W2122904379","https://openalex.org/W2135192531","https://openalex.org/W2137052779","https://openalex.org/W2138275182","https://openalex.org/W2251756410","https://openalex.org/W2251957306","https://openalex.org/W2264517602","https://openalex.org/W2346578521","https://openalex.org/W2485374661","https://openalex.org/W2584239330","https://openalex.org/W2619099103","https://openalex.org/W2964167098"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032","https://openalex.org/W2382997850"],"abstract_inverted_index":{"With":[0],"the":[1,28,36,40,45,48,54,57,75,79,88,94,118,157,162,178,183,195,205,209,235,238,247,251,261,264,270,275,283,289],"recent":[2],"revival":[3],"of":[4,32,44,56,90,102,127,174,187,263,279],"interest":[5],"in":[6,78,233,242,282],"deep":[7,16,33],"neural":[8,34,80],"networks,":[9,35],"many":[10],"studies":[11],"have":[12,225],"focused":[13],"on":[14,38,64],"exploring":[15],"learning":[17],"methods":[18],"for":[19,66,121,152,156,177,220],"automatic":[20],"DDIs":[21,67],"(Drug-drug":[22],"Interactions)":[23],"extraction.":[24,68],"However,":[25],"due":[26],"to":[27,73,86,116,149,170,190,259,273],"\u201cblack":[29],"box\u201d":[30],"nature":[31],"researches":[37],"discussing":[39],"interpretability":[41,55],"and":[42,135,208,292],"reliability":[43],"output":[46],"from":[47],"models":[49],"still":[50],"fall":[51],"short.":[52],"Considering":[53],"output,":[58],"we":[59,107,198,215,268],"propose":[60],"a":[61,99,109,142,166,217],"model":[62,70,95,104,125,229],"based":[63],"mechanism":[65,169],"Our":[69,124],"is":[71,105],"able":[72],"compute":[74],"importance":[76],"scores":[77],"network,":[81],"which":[82,286],"can":[83,287],"be":[84],"utilized":[85],"measure":[87],"contributions":[89,173],"different":[91,172],"words":[92],"while":[93],"makes":[96],"decision.":[97],"Besides,":[98],"key":[100],"feature":[101],"our":[103,228],"that":[106,227],"design":[108],"classified":[110,179],"tag":[111,180,272],"word,":[112,154],"named":[113],"as":[114],"[CLS],":[115],"learn":[117,150,171,274],"global":[119,192,276],"information":[120,193,277],"DDI":[122],"classification.":[123,221],"consists":[126],"three":[128],"layers,":[129],"including":[130],"Bi-LSTM":[131,139,206],"layer,":[132,185,211,285],"attention":[133,163,168,210,248],"layer":[134,140,164,207],"dense":[136,184,284],"Layer.":[137],"The":[138,222],"uses":[141],"bi-directional":[143],"long":[144],"short":[145],"term":[146],"memory":[147],"network":[148],"embeddings":[151],"each":[153,175],"also":[155,293],"[CLS]":[158,201,271],"tag.":[159],"We":[160],"equip":[161],"with":[165,250],"multi-head":[167],"work":[176],"word.":[181],"In":[182],"instead":[186,278],"performing":[188,280],"pooling":[189,281],"capture":[191],"across":[194],"whole":[196],"sentence,":[197],"combine":[199],"two":[200,239],"tags":[202],"produced":[203],"by":[204],"respectively.":[212],"At":[213],"last,":[214],"use":[216,269],"Softmax":[218],"function":[219],"experimental":[223],"results":[224],"shown":[226],"has":[230],"competitive":[231],"advantage":[232],"extract":[234],"relation":[236],"between":[237],"candidate":[240],"drugs":[241],"one":[243],"instance.":[244],"By":[245],"visualizing":[246],"weights":[249],"corresponding":[252],"instance,":[253],"it":[254],"offers":[255],"an":[256],"intuitive":[257],"way":[258],"understand":[260],"basis":[262],"classification":[265],"results.":[266],"Moreover,":[267],"reduce":[288],"training":[290],"time":[291],"improves":[294],"performance.":[295]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
