{"id":"https://openalex.org/W3054687810","doi":"https://doi.org/10.1109/iske47853.2019.9170351","title":"Knowledge-Aware LSTM for Machine Comprehension","display_name":"Knowledge-Aware LSTM for Machine Comprehension","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3054687810","doi":"https://doi.org/10.1109/iske47853.2019.9170351","mag":"3054687810"},"language":"en","primary_location":{"id":"doi:10.1109/iske47853.2019.9170351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske47853.2019.9170351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100452098","display_name":"Zhuang Liu","orcid":"https://orcid.org/0000-0002-4695-6345"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuang Liu","raw_affiliation_strings":["Dalian University of Technology,School of Computer Science and Technology,Dalian,China","School of Computer Science and Technology, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology,School of Computer Science and Technology,Dalian,China","institution_ids":["https://openalex.org/I27357992"]},{"raw_affiliation_string":"School of Computer Science and Technology, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031577422","display_name":"Kaiyu Huang","orcid":"https://orcid.org/0000-0001-6779-1810"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaiyu Huang","raw_affiliation_strings":["Dalian University of Technology,School of Computer Science and Technology,Dalian,China","School of Computer Science and Technology, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology,School of Computer Science and Technology,Dalian,China","institution_ids":["https://openalex.org/I27357992"]},{"raw_affiliation_string":"School of Computer Science and Technology, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103032768","display_name":"Ziyu Gao","orcid":"https://orcid.org/0009-0004-7056-7130"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyu Gao","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,International School,Beijing,China","International School, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,International School,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"International School, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046871248","display_name":"Degen Huang","orcid":"https://orcid.org/0000-0002-8860-7805"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Degen Huang","raw_affiliation_strings":["Dalian University of Technology,School of Computer Science and Technology,Dalian,China","School of Computer Science and Technology, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology,School of Computer Science and Technology,Dalian,China","institution_ids":["https://openalex.org/I27357992"]},{"raw_affiliation_string":"School of Computer Science and Technology, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1273","last_page":"1281"},"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":0.9969000220298767,"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":0.996399998664856,"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/interpretability","display_name":"Interpretability","score":0.8760613203048706},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8672620058059692},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6512874960899353},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.636425256729126},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6275280117988586},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5306348204612732},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.519749641418457},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3817015588283539}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8760613203048706},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8672620058059692},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6512874960899353},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.636425256729126},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6275280117988586},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5306348204612732},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.519749641418457},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3817015588283539},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iske47853.2019.9170351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske47853.2019.9170351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8700000047683716}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1533230146","https://openalex.org/W1544827683","https://openalex.org/W2064675550","https://openalex.org/W2125436846","https://openalex.org/W2127795553","https://openalex.org/W2417356443","https://openalex.org/W2476140796","https://openalex.org/W2507756961","https://openalex.org/W2516196286","https://openalex.org/W2521709538","https://openalex.org/W2551396370","https://openalex.org/W2552027021","https://openalex.org/W2600024417","https://openalex.org/W2604368306","https://openalex.org/W2739749670","https://openalex.org/W2740747242","https://openalex.org/W2742122443","https://openalex.org/W2750557179","https://openalex.org/W2763186733","https://openalex.org/W2798416089","https://openalex.org/W2949615363","https://openalex.org/W2962808855","https://openalex.org/W2962985038","https://openalex.org/W2963019137","https://openalex.org/W2963223524","https://openalex.org/W2963290255","https://openalex.org/W2963344337","https://openalex.org/W2963393262","https://openalex.org/W2963595025","https://openalex.org/W2963748441","https://openalex.org/W2963829073","https://openalex.org/W2963871484","https://openalex.org/W2964064432","https://openalex.org/W2964185324","https://openalex.org/W3029462071","https://openalex.org/W3104486441","https://openalex.org/W4297749157","https://openalex.org/W4394665226","https://openalex.org/W6631964550","https://openalex.org/W6632455782","https://openalex.org/W6678830454","https://openalex.org/W6678890848","https://openalex.org/W6720997899","https://openalex.org/W6725207838","https://openalex.org/W6729263887","https://openalex.org/W6729322275","https://openalex.org/W6729654139","https://openalex.org/W6735889696","https://openalex.org/W6736868252","https://openalex.org/W6741730259","https://openalex.org/W6744175107","https://openalex.org/W6748270630","https://openalex.org/W6752345439","https://openalex.org/W6777932488","https://openalex.org/W6864315806"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W2809283485","https://openalex.org/W4293768783","https://openalex.org/W4288347394"],"abstract_inverted_index":{"Machine":[0],"Comprehension":[1],"(MC)":[2],"of":[3,50],"text":[4],"is":[5,39,123,140],"the":[6,44,100,150,184,200],"problem":[7],"to":[8,53,74,79,85,109,113,115,174],"answer":[9],"a":[10,14,61,141],"query":[11],"based":[12],"on":[13,33,43,199,207,216,250,265],"given":[15],"document.":[16],"Although":[17],"MC":[18,90,202,235,253,266],"has":[19],"been":[20],"very":[21],"popular":[22,232],"recently,":[23],"it":[24],"still":[25],"have":[26],"some":[27],"serious":[28],"weaknesses":[29],"which":[30,118,139],"rely":[31],"only":[32],"query-to-document":[34],"interaction":[35,165],"or":[36],"its":[37],"learning":[38],"just":[40],"heavily":[41],"dependent":[42],"training":[45],"data.":[46],"To":[47,92],"take":[48],"advantage":[49],"external":[51,81,121,157,261],"knowledge":[52,63,82,122,129,159,240,262],"improve":[54,86],"neural":[55,66,87,131,146,234,258],"networks":[56,88],"for":[57,89,243],"MC,":[58,245],"we":[59,126,228],"propose":[60],"novel":[62,142],"enhanced":[64,130],"recurrent":[65],"model,":[67],"called":[68,133],"knowledge-aware":[69,143],"LSTM":[70,76],"(k-LSTM),":[71],"an":[72,105,187],"extension":[73],"basic":[75],"cells,":[77],"designed":[78],"exploit":[80],"bases":[83],"(KBs)":[84],"task.":[91,267],"incorporate":[93],"KBs":[94,116],"with":[95,260],"contextual":[96],"information":[97,119],"effectively":[98,172],"from":[99,120,183],"currently":[101],"text,":[102],"k-LSTM":[103,151,238],"employs":[104],"compositional":[106,144,163],"attention":[107,145,164],"mechanism":[108],"adaptively":[110],"decide":[111],"whether":[112],"attend":[114],"and":[117,161,197,211,222,246],"useful.":[124],"Furthermore,":[125],"present":[127],"our":[128,153,192],"network,":[132],"Knowledge-guided":[134],"DIM":[135],"Reader":[136,171],"(K-DIM":[137],"Reader),":[138],"network":[147],"architecture,":[148],"employing":[149],"in":[152,186],"framework.":[154],"By":[155],"stringing":[156],"background":[158],"together":[160],"imposing":[162],"that":[166,179,257],"regulate":[167],"their":[168,248],"interaction,":[169],"K-DIM":[170],"learns":[173],"perform":[175],"reading":[176],"comprehension":[177],"processes":[178],"are":[180],"directly":[181],"inferred":[182],"data":[185],"end-to-end":[188,233],"approach.":[189],"We":[190,255],"show":[191],"proposed":[193],"models":[194,236,242],"strength,":[195],"robustness":[196],"interpretability":[198],"challenging":[201],"datasets,":[203,219],"achieving":[204],"significant":[205],"improvements":[206],"SQuAD":[208],"dataset":[209],"[1]":[210],"obtaining":[212],"new":[213],"state-of-the-art":[214],"results":[215],"both":[217,251],"Cloze-style":[218],"CBTest":[220],"[2]":[221],"CNN":[223],"news":[224],"[3].":[225],"In":[226],"particular,":[227],"further":[229],"extend":[230],"6":[231],"using":[237],"incorporating":[239],"into":[241],"improving":[244],"evaluate":[247],"performance":[249,264],"well-known":[252],"datasets.":[254],"demonstrate":[256],"model":[259],"improves":[263]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}