{"id":"https://openalex.org/W2889874042","doi":"https://doi.org/10.18653/v1/d18-1183","title":"Neural Multitask Learning for Simile Recognition","display_name":"Neural Multitask Learning for Simile Recognition","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2889874042","doi":"https://doi.org/10.18653/v1/d18-1183","mag":"2889874042"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d18-1183","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1183","pdf_url":"https://www.aclweb.org/anthology/D18-1183.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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D18-1183.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101626332","display_name":"Lizhen Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lizhen Liu","raw_affiliation_strings":["Information Engineering, Capital Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Information Engineering, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072904902","display_name":"Xiao Hu","orcid":"https://orcid.org/0000-0001-7668-4689"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Hu","raw_affiliation_strings":["Information Engineering, Capital Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Information Engineering, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101884750","display_name":"Wei Song","orcid":"https://orcid.org/0000-0003-2334-3623"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Song","raw_affiliation_strings":["Information Engineering, Capital Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Information Engineering, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102364010","display_name":"Ruiji Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruiji Fu","raw_affiliation_strings":["iFLYTEK Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"iFLYTEK Research, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418165","display_name":"Ting Liu","orcid":"https://orcid.org/0000-0003-3489-4578"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Liu","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076447478","display_name":"Guoping Hu","orcid":"https://orcid.org/0000-0002-7939-4588"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guoping Hu","raw_affiliation_strings":["iFLYTEK Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"iFLYTEK Research, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101626332"],"corresponding_institution_ids":["https://openalex.org/I96852419"],"apc_list":null,"apc_paid":null,"fwci":2.8771,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.92828146,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1543","last_page":"1553"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10028","display_name":"Topic Modeling","score":0.9986000061035156,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/simile","display_name":"Simile","score":0.9970602989196777},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6789681911468506},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6339274048805237},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5707867741584778},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5607208609580994},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4967842400074005},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49454566836357117},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4332558512687683},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3733975291252136},{"id":"https://openalex.org/keywords/metaphor","display_name":"Metaphor","score":0.2600494623184204},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1866835355758667}],"concepts":[{"id":"https://openalex.org/C2780139471","wikidata":"https://www.wikidata.org/wiki/Q199714","display_name":"Simile","level":3,"score":0.9970602989196777},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6789681911468506},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6339274048805237},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5707867741584778},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5607208609580994},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4967842400074005},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49454566836357117},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4332558512687683},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3733975291252136},{"id":"https://openalex.org/C2778311575","wikidata":"https://www.wikidata.org/wiki/Q18534","display_name":"Metaphor","level":2,"score":0.2600494623184204},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1866835355758667},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d18-1183","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1183","pdf_url":"https://www.aclweb.org/anthology/D18-1183.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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d18-1183","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1183","pdf_url":"https://www.aclweb.org/anthology/D18-1183.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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.699999988079071}],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3744313044","display_name":null,"funder_award_id":"Social","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3866723802","display_name":null,"funder_award_id":"201703","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5063481269","display_name":null,"funder_award_id":"61876113","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5939423041","display_name":null,"funder_award_id":"Technology","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G633984120","display_name":null,"funder_award_id":"201610","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G852339338","display_name":null,"funder_award_id":"2017032","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2889874042.pdf","grobid_xml":"https://content.openalex.org/works/W2889874042.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W56200336","https://openalex.org/W1516142451","https://openalex.org/W1614298861","https://openalex.org/W1640287562","https://openalex.org/W1863780671","https://openalex.org/W1996908104","https://openalex.org/W2004763266","https://openalex.org/W2016043834","https://openalex.org/W2050797400","https://openalex.org/W2052417512","https://openalex.org/W2064675550","https://openalex.org/W2095705004","https://openalex.org/W2117130368","https://openalex.org/W2126176114","https://openalex.org/W2131774270","https://openalex.org/W2133564696","https://openalex.org/W2147880316","https://openalex.org/W2150582633","https://openalex.org/W2155067589","https://openalex.org/W2156884493","https://openalex.org/W2250379095","https://openalex.org/W2251267267","https://openalex.org/W2251559320","https://openalex.org/W2296283641","https://openalex.org/W2311095070","https://openalex.org/W2357209558","https://openalex.org/W2384495648","https://openalex.org/W2407776548","https://openalex.org/W2470742932","https://openalex.org/W2511080464","https://openalex.org/W2587227081","https://openalex.org/W2592170186","https://openalex.org/W2785707555","https://openalex.org/W2963153906","https://openalex.org/W2963706742","https://openalex.org/W2964167098","https://openalex.org/W2964308564"],"related_works":["https://openalex.org/W2958367604","https://openalex.org/W3132692330","https://openalex.org/W2746576560","https://openalex.org/W2870601762","https://openalex.org/W4320035835","https://openalex.org/W2360749238","https://openalex.org/W2100992737","https://openalex.org/W2795799933","https://openalex.org/W3123558400","https://openalex.org/W2279372215"],"abstract_inverted_index":{"Simile":[0,20],"is":[1,22,124],"a":[2,40,62,66],"special":[3],"type":[4],"of":[5,42,57],"metaphor,":[6],"where":[7],"comparators":[8],"such":[9],"as":[10,13],"like":[11],"and":[12,27,34,81,98,105],"are":[14],"used":[15],"to":[16,23],"compare":[17],"two":[18],"objects.":[19],"recognition":[21,44],"recognize":[24],"simile":[25,29,43,75,78,102,106],"sentences":[26,59],"extract":[28],"components,":[30],"i.e.,":[31],"the":[32,35,89,122],"tenor":[33],"vehicle.":[36],"This":[37],"paper":[38],"presents":[39],"study":[41],"in":[45],"Chinese.":[46],"We":[47,64],"construct":[48],"an":[49],"annotated":[50],"corpus":[51],"for":[52,70],"this":[53],"research,":[54],"which":[55],"consists":[56],"11.3k":[58],"that":[60,88],"contain":[61],"comparator.":[63],"propose":[65],"neural":[67,90],"network":[68,91],"framework":[69],"jointly":[71],"optimizing":[72],"three":[73],"tasks:":[74],"sentence":[76,103],"classification,":[77],"component":[79,107],"extraction":[80,108],"language":[82],"modeling.":[83],"The":[84,114],"experimental":[85],"results":[86],"show":[87],"based":[92],"approaches":[93],"can":[94,109,116],"outperform":[95],"all":[96],"rule-based":[97],"feature-based":[99],"baselines.":[100],"Both":[101],"classification":[104],"benefit":[110],"from":[111],"multitask":[112],"learning.":[113],"former":[115],"be":[117],"solved":[118],"very":[119],"well,":[120],"while":[121],"latter":[123],"more":[125],"difficult.":[126]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":4}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
