{"id":"https://openalex.org/W2985115890","doi":"https://doi.org/10.1145/3357384.3358071","title":"Knowledge-aware Textual Entailment with Graph Attention Network","display_name":"Knowledge-aware Textual Entailment with Graph Attention Network","publication_year":2019,"publication_date":"2019-11-03","ids":{"openalex":"https://openalex.org/W2985115890","doi":"https://doi.org/10.1145/3357384.3358071","mag":"2985115890"},"language":"en","primary_location":{"id":"doi:10.1145/3357384.3358071","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357384.3358071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","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/A5090695897","display_name":"Daoyuan Chen","orcid":"https://orcid.org/0000-0002-8015-2121"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Daoyuan Chen","raw_affiliation_strings":["Peking University Shenzhen Graduate School, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University Shenzhen Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046576694","display_name":"Yaliang Li","orcid":"https://orcid.org/0000-0002-4204-6096"},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]},{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yaliang Li","raw_affiliation_strings":["Alibaba Group, Bellevue, WA, USA"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Bellevue, WA, USA","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083369457","display_name":"Min Yang","orcid":"https://orcid.org/0000-0001-7345-5071"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Yang","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022672030","display_name":"Hai-Tao Zheng","orcid":"https://orcid.org/0000-0001-5128-5649"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai-Tao Zheng","raw_affiliation_strings":["Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074799043","display_name":"Ying Shen","orcid":"https://orcid.org/0000-0002-3220-904X"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Shen","raw_affiliation_strings":["Peking University Shenzhen Graduate School, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University Shenzhen Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5090695897"],"corresponding_institution_ids":["https://openalex.org/I4210128628"],"apc_list":null,"apc_paid":null,"fwci":0.8401,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.80821622,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2145","last_page":"2148"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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":0.9994999766349792,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9962000250816345,"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/textual-entailment","display_name":"Textual entailment","score":0.9216470718383789},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8030943274497986},{"id":"https://openalex.org/keywords/logical-consequence","display_name":"Logical consequence","score":0.6757710576057434},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6621667742729187},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6504544615745544},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.573157012462616},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.4593404531478882},{"id":"https://openalex.org/keywords/text-graph","display_name":"Text graph","score":0.45063111186027527},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4418705701828003},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41812416911125183},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4159690737724304},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.19069722294807434},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.10719582438468933}],"concepts":[{"id":"https://openalex.org/C95318506","wikidata":"https://www.wikidata.org/wiki/Q6588467","display_name":"Textual entailment","level":3,"score":0.9216470718383789},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8030943274497986},{"id":"https://openalex.org/C134752490","wikidata":"https://www.wikidata.org/wiki/Q374182","display_name":"Logical consequence","level":2,"score":0.6757710576057434},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6621667742729187},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6504544615745544},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.573157012462616},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4593404531478882},{"id":"https://openalex.org/C66945725","wikidata":"https://www.wikidata.org/wiki/Q18388823","display_name":"Text graph","level":3,"score":0.45063111186027527},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4418705701828003},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41812416911125183},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4159690737724304},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.19069722294807434},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.10719582438468933},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3357384.3358071","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357384.3358071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8399999737739563,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G1614098183","display_name":null,"funder_award_id":"61602013","funder_id":"https://openalex.org/F4320327720","funder_display_name":"Foundation for Innovative Research Groups of the National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320327720","display_name":"Foundation for Innovative Research Groups of the National Natural Science Foundation of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W205765513","https://openalex.org/W2084009247","https://openalex.org/W2798416089","https://openalex.org/W2890894339","https://openalex.org/W2962767366","https://openalex.org/W2964294651"],"related_works":["https://openalex.org/W12963412","https://openalex.org/W2250460949","https://openalex.org/W3158371345","https://openalex.org/W3141423438","https://openalex.org/W2071098659","https://openalex.org/W2627035043","https://openalex.org/W4385571113","https://openalex.org/W1553238488","https://openalex.org/W1988872758","https://openalex.org/W4378603571"],"abstract_inverted_index":{"Textual":[0,97],"entailment":[1,39,67,126],"is":[2],"a":[3,13,94,119],"central":[4],"problem":[5],"of":[6,15,24,62,74],"language":[7,29],"variability,":[8],"which":[9,129],"has":[10],"been":[11,35],"attracting":[12],"lot":[14],"interest":[16],"and":[17,84,133,138],"it":[18],"poses":[19],"significant":[20],"issues":[21],"in":[22],"front":[23],"systems":[25],"aimed":[26],"at":[27],"natural":[28],"understanding.":[30],"Recently,":[31],"various":[32],"frameworks":[33],"have":[34],"proposed":[36],"for":[37,123],"textual":[38,66],"recognition,":[40],"ranging":[41],"from":[42],"traditional":[43],"computational":[44],"linguistics":[45],"techniques":[46],"to":[47],"deep":[48,55],"learning":[49],"model":[50],"based":[51,125],"methods.":[52,156],"However,":[53],"recent":[54],"neural":[56,124],"networks":[57],"that":[58,101,151],"achieve":[59],"the":[60,63,71,75,80,87,90,131,142,147,154],"state":[61],"art":[64],"on":[65,141,146],"task":[68],"only":[69],"consider":[70],"context":[72],"information":[73,83],"given":[76],"sentences":[77],"rather":[78],"than":[79],"real-world":[81],"background":[82],"knowledge":[85,110],"beyond":[86],"context.":[88],"In":[89],"paper,":[91],"we":[92],"propose":[93,118],"Knowledge-Context":[95],"Interactive":[96],"Entailment":[98],"Network":[99],"(KCI-TEN)":[100],"learns":[102],"graph":[103,111,113],"level":[104],"sentence":[105],"representations":[106],"by":[107],"harnessing":[108],"external":[109],"with":[112,135],"attention":[114],"network.":[115],"We":[116],"further":[117],"text-graph":[120],"interaction":[121],"mechanism":[122],"matching":[127],"learning,":[128],"endows":[130],"redundancy":[132],"noise":[134],"less":[136],"importance":[137],"put":[139],"emphasis":[140],"informative":[143],"representations.":[144],"Experiments":[145],"SciTail":[148],"dataset":[149],"demonstrate":[150],"KCI-TEN":[152],"outperforms":[153],"state-of-the-art":[155]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}