{"id":"https://openalex.org/W2512531235","doi":"https://doi.org/10.18653/v1/p16-1098","title":"Deep Fusion LSTMs for Text Semantic Matching","display_name":"Deep Fusion LSTMs for Text Semantic Matching","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2512531235","doi":"https://doi.org/10.18653/v1/p16-1098","mag":"2512531235"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p16-1098","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1098","pdf_url":"https://www.aclweb.org/anthology/P16-1098.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 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P16-1098.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100355025","display_name":"Pengfei Liu","orcid":"https://orcid.org/0009-0008-6932-7091"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengfei Liu","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, Fudan University School of Computer Science, Fudan University 825 Zhangheng Road, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, Fudan University School of Computer Science, Fudan University 825 Zhangheng Road, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044665993","display_name":"Xipeng Qiu","orcid":"https://orcid.org/0000-0001-7163-5247"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xipeng Qiu","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, Fudan University School of Computer Science, Fudan University 825 Zhangheng Road, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, Fudan University School of Computer Science, Fudan University 825 Zhangheng Road, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103130791","display_name":"Jifan Chen","orcid":"https://orcid.org/0000-0001-6814-0999"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jifan Chen","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, Fudan University School of Computer Science, Fudan University 825 Zhangheng Road, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, Fudan University School of Computer Science, Fudan University 825 Zhangheng Road, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088834359","display_name":"Xuanjing Huang","orcid":"https://orcid.org/0000-0001-9197-9426"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuanjing Huang","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, Fudan University School of Computer Science, Fudan University 825 Zhangheng Road, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, Fudan University School of Computer Science, Fudan University 825 Zhangheng Road, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":8.5417,"has_fulltext":true,"cited_by_count":67,"citation_normalized_percentile":{"value":0.98399073,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1034","last_page":"1043"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9997000098228455,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9911999702453613,"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":0.799014151096344},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7065425515174866},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.680640459060669},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5881091952323914},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5725507736206055},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5460600256919861},{"id":"https://openalex.org/keywords/semantic-matching","display_name":"Semantic matching","score":0.4320750832557678},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11542972922325134}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.799014151096344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7065425515174866},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.680640459060669},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5881091952323914},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5725507736206055},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5460600256919861},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.4320750832557678},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11542972922325134},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/p16-1098","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1098","pdf_url":"https://www.aclweb.org/anthology/P16-1098.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 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p16-1098","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1098","pdf_url":"https://www.aclweb.org/anthology/P16-1098.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 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1979465396","display_name":"\u878d\u5408\u6587\u672c\u5185\u5bb9\u4e0e\u7ed3\u6784\u4fe1\u606f\u7684\u8bdd\u9898\u5206\u6790\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61472088","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2711593179","display_name":null,"funder_award_id":"61473092","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3892115987","display_name":null,"funder_award_id":"61532011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7433387973","display_name":null,"funder_award_id":"2015AA015408","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/W2512531235.pdf","grobid_xml":"https://content.openalex.org/works/W2512531235.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W196214544","https://openalex.org/W581956982","https://openalex.org/W1544827683","https://openalex.org/W1685006559","https://openalex.org/W1771459135","https://openalex.org/W1793121960","https://openalex.org/W1810943226","https://openalex.org/W1840435438","https://openalex.org/W1909234690","https://openalex.org/W2064675550","https://openalex.org/W2103305545","https://openalex.org/W2110485445","https://openalex.org/W2118463056","https://openalex.org/W2125930537","https://openalex.org/W2127426251","https://openalex.org/W2127795553","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2146502635","https://openalex.org/W2170738476","https://openalex.org/W2170942820","https://openalex.org/W2211192759","https://openalex.org/W2227303133","https://openalex.org/W2250539671","https://openalex.org/W2251189452","https://openalex.org/W2251427843","https://openalex.org/W2265289447","https://openalex.org/W2267186426","https://openalex.org/W2282146481","https://openalex.org/W2286300105","https://openalex.org/W2291880741","https://openalex.org/W2294860948","https://openalex.org/W2949615363","https://openalex.org/W2949989304","https://openalex.org/W2950527759","https://openalex.org/W2951008357","https://openalex.org/W2951359136","https://openalex.org/W2962958286","https://openalex.org/W2962965465","https://openalex.org/W2963053846","https://openalex.org/W2963542836","https://openalex.org/W2964308564","https://openalex.org/W4254816979","https://openalex.org/W4303633609"],"related_works":["https://openalex.org/W2373213638","https://openalex.org/W2380556669","https://openalex.org/W2179503532","https://openalex.org/W2380389143","https://openalex.org/W64465677","https://openalex.org/W3003836728","https://openalex.org/W3037084154","https://openalex.org/W2108395123","https://openalex.org/W2890190347","https://openalex.org/W2586236392"],"abstract_inverted_index":{"Recently,":[0],"there":[1],"is":[2],"rising":[3],"interest":[4],"in":[5,36],"modelling":[6],"the":[7,30,55,66,84],"interactions":[8],"of":[9,23,33,44,49,57,68,86,97],"text":[10,34],"pair":[11,35],"with":[12],"deep":[13,24],"neural":[14],"networks.":[15],"In":[16],"this":[17],"paper,":[18],"we":[19,91],"propose":[20],"a":[21,37,52],"model":[22,29,106],"fusion":[25],"LSTMs":[26],"(DF-LSTMs)":[27],"to":[28,64],"strong":[31],"interaction":[32],"recursive":[38],"matching":[39,75],"way.":[40],"Specifically,":[41],"DF-LSTMs":[42],"consist":[43],"two":[45,79],"interdependent":[46],"LSTMs,":[47,69],"each":[48],"which":[50],"models":[51],"sequence":[53],"under":[54],"influence":[56],"another.":[58],"We":[59],"also":[60],"use":[61],"external":[62],"memory":[63],"increase":[65],"capacity":[67],"thereby":[70],"possibly":[71],"capturing":[72],"more":[73],"complicated":[74],"patterns.":[76],"Experiments":[77],"on":[78],"very":[80],"large":[81],"datasets":[82],"demonstrate":[83],"efficacy":[85],"our":[87,98,105],"proposed":[88],"architecture.":[89],"Furthermore,":[90],"present":[92],"an":[93,101],"elaborate":[94],"qualitative":[95],"analysis":[96],"models,":[99],"giving":[100],"intuitive":[102],"understanding":[103],"how":[104],"worked.":[107]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":25},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
