{"id":"https://openalex.org/W2911484884","doi":"https://doi.org/10.1109/ialp.2018.8629139","title":"Classifying Temporal Relations Between Events by Deep BiLSTM","display_name":"Classifying Temporal Relations Between Events by Deep BiLSTM","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2911484884","doi":"https://doi.org/10.1109/ialp.2018.8629139","mag":"2911484884"},"language":"en","primary_location":{"id":"doi:10.1109/ialp.2018.8629139","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ialp.2018.8629139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 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/A5100610198","display_name":"Yijie Zhang","orcid":"https://orcid.org/0000-0003-1594-1789"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yijie Zhang","raw_affiliation_strings":["Natural Language Processing Lab, School of Computer Science and Technology Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"Natural Language Processing Lab, School of Computer Science and Technology Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100695549","display_name":"Peifeng Li","orcid":"https://orcid.org/0000-0003-4850-3128"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peifeng Li","raw_affiliation_strings":["Natural Language Processing Lab, School of Computer Science and Technology Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"Natural Language Processing Lab, School of Computer Science and Technology Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012794465","display_name":"Guodong Zhou","orcid":"https://orcid.org/0000-0002-7887-5099"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guodong Zhou","raw_affiliation_strings":["Natural Language Processing Lab, School of Computer Science and Technology Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"Natural Language Processing Lab, School of Computer Science and Technology Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100610198"],"corresponding_institution_ids":["https://openalex.org/I3923682"],"apc_list":null,"apc_paid":null,"fwci":1.1643,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.80808541,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"267","last_page":"272"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11719","display_name":"Data Quality and Management","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9959999918937683,"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":0.7883498668670654},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6872480511665344},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.58784419298172},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.558471143245697},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5574519634246826},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.5495674014091492},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5169186592102051},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.4980320930480957},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.45442843437194824},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4166937470436096},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3978084325790405},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38164034485816956},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33204174041748047},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.23818418383598328}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7883498668670654},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6872480511665344},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.58784419298172},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.558471143245697},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5574519634246826},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5495674014091492},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5169186592102051},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.4980320930480957},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.45442843437194824},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4166937470436096},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3978084325790405},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38164034485816956},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33204174041748047},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.23818418383598328},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ialp.2018.8629139","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ialp.2018.8629139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Asian Language Processing (IALP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W30314283","https://openalex.org/W77146693","https://openalex.org/W1522301498","https://openalex.org/W1614298861","https://openalex.org/W1990886313","https://openalex.org/W2064675550","https://openalex.org/W2081580037","https://openalex.org/W2112251443","https://openalex.org/W2135586429","https://openalex.org/W2140244223","https://openalex.org/W2157275230","https://openalex.org/W2168336840","https://openalex.org/W2185599447","https://openalex.org/W2236688737","https://openalex.org/W2251325107","https://openalex.org/W2251607656","https://openalex.org/W2251873637","https://openalex.org/W2561222820","https://openalex.org/W2575365684","https://openalex.org/W2603270557","https://openalex.org/W2741237963","https://openalex.org/W2741502284","https://openalex.org/W2771336514","https://openalex.org/W2950577311","https://openalex.org/W2963501608","https://openalex.org/W2964087600","https://openalex.org/W2964121744","https://openalex.org/W2964217331","https://openalex.org/W6601179756","https://openalex.org/W6603149634","https://openalex.org/W6681234702","https://openalex.org/W6682976278","https://openalex.org/W6689876912","https://openalex.org/W6691596409","https://openalex.org/W6731735555","https://openalex.org/W6746424391"],"related_works":["https://openalex.org/W4234874385","https://openalex.org/W2323648130","https://openalex.org/W2157140558","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W3000197790","https://openalex.org/W4315865067","https://openalex.org/W2979433843","https://openalex.org/W3208304128"],"abstract_inverted_index":{"Neural":[0],"networks":[1,58],"illustrate":[2],"their":[3],"advantages":[4],"in":[5,30,65],"comparison":[6],"with":[7],"traditional":[8],"classifier-based":[9],"methods":[10],"for":[11,81],"event":[12,62],"temporal":[13,63],"relation":[14],"classification.":[15],"However,":[16],"most":[17],"of":[18,36,73],"them":[19],"may":[20],"not":[21],"be":[22],"able":[23],"to":[24,51,60],"explore":[25],"the":[26,31,37,71,79,82,96,103],"deep":[27,53],"semantic":[28],"representation":[29],"larger":[32],"hypothesis":[33],"space":[34],"because":[35],"shallow":[38],"architectures":[39],"(e.g.,":[40],"one-layer":[41],"CNN":[42],"or":[43],"RNN).":[44],"To":[45],"address":[46],"this":[47,66],"issue,":[48],"we":[49,69],"propose":[50],"use":[52],"bidirectional":[54],"long":[55],"short-term":[56],"memory":[57],"(DBiLSTMs)":[59],"classify":[61],"relations":[64],"paper,":[67],"where":[68],"concatenate":[70],"outputs":[72],"all":[74],"prior":[75],"layers":[76],"together":[77],"as":[78],"input":[80],"subsequent":[83],"layer.":[84],"The":[85],"experimental":[86],"results":[87],"on":[88],"TimeBank-Dense":[89],"and":[90],"Richer":[91],"Event":[92],"Description":[93],"indicate":[94],"that":[95],"proposed":[97],"DBiLSTMs":[98],"has":[99],"outstanding":[100],"performance":[101],"over":[102],"state-of-the-art":[104],"methods.":[105]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
