{"id":"https://openalex.org/W3011077506","doi":"https://doi.org/10.1109/ialp48816.2019.9037671","title":"Duplicate Question Detection based on Neural Networks and Multi-head Attention","display_name":"Duplicate Question Detection based on Neural Networks and Multi-head Attention","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3011077506","doi":"https://doi.org/10.1109/ialp48816.2019.9037671","mag":"3011077506"},"language":"en","primary_location":{"id":"doi:10.1109/ialp48816.2019.9037671","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ialp48816.2019.9037671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Asian Language Processing (IALP)","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/A5031674072","display_name":"Heng Zhang","orcid":"https://orcid.org/0000-0002-1093-5809"},"institutions":[{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]},{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Zhang","raw_affiliation_strings":["Shanghai Key Laboratory of Trustworthy Computing East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Trustworthy Computing East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I4210139618","https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100780219","display_name":"Liangyu Chen","orcid":"https://orcid.org/0000-0003-0394-6208"},"institutions":[{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]},{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangyu Chen","raw_affiliation_strings":["Shanghai Key Laboratory of Trustworthy Computing East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Trustworthy Computing East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I4210139618","https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4338,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.73782304,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9979000091552734,"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":0.9979000091552734,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9865000247955322,"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/computer-science","display_name":"Computer science","score":0.8162980079650879},{"id":"https://openalex.org/keywords/parallelizable-manifold","display_name":"Parallelizable manifold","score":0.7130522131919861},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6884902715682983},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6513626575469971},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5980490446090698},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5231733918190002},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.4903264343738556},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.47810977697372437},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4360865354537964},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42023709416389465},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3688596189022064},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.23891815543174744}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8162980079650879},{"id":"https://openalex.org/C148047603","wikidata":"https://www.wikidata.org/wiki/Q1014612","display_name":"Parallelizable manifold","level":2,"score":0.7130522131919861},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6884902715682983},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6513626575469971},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5980490446090698},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5231733918190002},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.4903264343738556},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.47810977697372437},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4360865354537964},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42023709416389465},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3688596189022064},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.23891815543174744},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ialp48816.2019.9037671","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ialp48816.2019.9037671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Asian Language Processing (IALP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1522301498","https://openalex.org/W1554663460","https://openalex.org/W1799366690","https://openalex.org/W1970875273","https://openalex.org/W2112796928","https://openalex.org/W2127589108","https://openalex.org/W2133564696","https://openalex.org/W2157331557","https://openalex.org/W2194775991","https://openalex.org/W2250539671","https://openalex.org/W2466490286","https://openalex.org/W2566770969","https://openalex.org/W2578328577","https://openalex.org/W2753410294","https://openalex.org/W2786109915","https://openalex.org/W2964121744","https://openalex.org/W2964245140","https://openalex.org/W2964308564","https://openalex.org/W4388297464","https://openalex.org/W6631190155","https://openalex.org/W6638444622","https://openalex.org/W6679434410","https://openalex.org/W6732428687","https://openalex.org/W6748668229"],"related_works":["https://openalex.org/W4285069850","https://openalex.org/W1974634278","https://openalex.org/W4240963716","https://openalex.org/W2891970004","https://openalex.org/W4301075503","https://openalex.org/W1596637634","https://openalex.org/W1996916724","https://openalex.org/W2321918740","https://openalex.org/W2900794160","https://openalex.org/W4288096837"],"abstract_inverted_index":{"It":[0],"is":[1,60,75,129],"well":[2],"known":[3],"that":[4,152],"using":[5],"only":[6],"one":[7],"neural":[8,31,58,95,125],"network":[9,59],"can":[10,158],"not":[11],"get":[12,110],"a":[13,105],"satisfied":[14],"accuracy":[15,154],"for":[16,38],"the":[17,55,64,117,134,137,153],"problem":[18],"of":[19,57,155],"Duplicate":[20],"Question":[21],"Detection.":[22],"In":[23,114],"order":[24],"to":[25,36,82,109,116,132],"break":[26],"through":[27],"this":[28],"dilemma,":[29],"different":[30,94,141],"networks":[32,96],"are":[33],"ensembled":[34],"serially":[35],"strive":[37],"better":[39,111],"accuracy.":[40,113],"However,":[41],"many":[42],"problems,":[43,87],"such":[44],"as":[45,97],"vanishing":[46],"gradient":[47],"or":[48,123],"exploding":[49],"gradient,":[50],"will":[51],"be":[52,68],"encountered":[53],"if":[54],"depth":[56],"blindly":[61],"increased.":[62],"Worse,":[63],"serial":[65],"integration":[66],"may":[67],"poor":[69],"in":[70,101,146],"computational":[71],"performance":[72,138],"since":[73],"it":[74],"less":[76],"parallelizable":[77],"and":[78,103,136],"needs":[79],"more":[80],"time":[81],"train.":[83],"To":[84],"solve":[85],"these":[86],"we":[88],"use":[89],"ensemble":[90],"learning":[91],"with":[92],"treating":[93],"individual":[98],"learners,":[99],"calculating":[100],"parallel,":[102],"proposing":[104],"new":[106],"voting":[107],"mechanism":[108],"detection":[112],"addition":[115],"classical":[118],"models":[119],"based":[120],"on":[121],"recurrent":[122],"convolutional":[124],"network,":[126],"Multi-Head":[127],"Attention":[128],"also":[130],"integrated":[131],"reduce":[133],"correlation":[135],"gap":[139],"between":[140],"models.":[142],"The":[143],"experimental":[144],"results":[145],"Quora":[147],"question":[148],"pairs":[149],"dataset":[150],"show":[151],"our":[156],"method":[157],"reach":[159],"89.3%.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}