{"id":"https://openalex.org/W2108380946","doi":"https://doi.org/10.1145/2396761.2398544","title":"Discovering logical knowledge for deep question answering","display_name":"Discovering logical knowledge for deep question answering","publication_year":2012,"publication_date":"2012-10-29","ids":{"openalex":"https://openalex.org/W2108380946","doi":"https://doi.org/10.1145/2396761.2398544","mag":"2108380946"},"language":"en","primary_location":{"id":"doi:10.1145/2396761.2398544","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2396761.2398544","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st 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/A5004413743","display_name":"Zhao Liu","orcid":"https://orcid.org/0000-0001-8951-5112"},"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":true,"raw_author_name":"Zhao Liu","raw_affiliation_strings":["Fudan Univeristy, Shanghai, China","[Fudan Univeristy, Shanghai, China]"],"affiliations":[{"raw_affiliation_string":"Fudan Univeristy, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"[Fudan Univeristy, 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":["Fudan Univeristy, Shanghai, China","[Fudan Univeristy, Shanghai, China]"],"affiliations":[{"raw_affiliation_string":"Fudan Univeristy, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"[Fudan Univeristy, Shanghai, China]","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100902259","display_name":"Ling Cao","orcid":null},"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":"Ling Cao","raw_affiliation_strings":["Fudan Univeristy, Shanghai, China","[Fudan Univeristy, Shanghai, China]"],"affiliations":[{"raw_affiliation_string":"Fudan Univeristy, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"[Fudan Univeristy, 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":["Fudan Univeristy, Shanghai, China","[Fudan Univeristy, Shanghai, China]"],"affiliations":[{"raw_affiliation_string":"Fudan Univeristy, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"[Fudan Univeristy, Shanghai, China]","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5004413743"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.4281,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.72961544,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1920","last_page":"1924"},"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":0.9994999766349792,"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/T12031","display_name":"Speech and dialogue systems","score":0.9855999946594238,"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/question-answering","display_name":"Question answering","score":0.8825337886810303},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7984569072723389},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6753247976303101},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.6218876838684082},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.587409496307373},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5483671426773071},{"id":"https://openalex.org/keywords/open-domain","display_name":"Open domain","score":0.5289195775985718},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.43150559067726135},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.4183200001716614},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.38815271854400635}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.8825337886810303},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7984569072723389},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6753247976303101},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.6218876838684082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.587409496307373},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5483671426773071},{"id":"https://openalex.org/C2993776861","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Open domain","level":3,"score":0.5289195775985718},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.43150559067726135},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.4183200001716614},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.38815271854400635}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2396761.2398544","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2396761.2398544","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st ACM international conference on Information and knowledge management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W11155487","https://openalex.org/W79548659","https://openalex.org/W1543747524","https://openalex.org/W1938740620","https://openalex.org/W1977970897","https://openalex.org/W1984626158","https://openalex.org/W1997945384","https://openalex.org/W2000545282","https://openalex.org/W2005148043","https://openalex.org/W2020549735","https://openalex.org/W2028175314","https://openalex.org/W2038324640","https://openalex.org/W2068737686","https://openalex.org/W2081580037","https://openalex.org/W2126034021","https://openalex.org/W2126851059","https://openalex.org/W2129967282","https://openalex.org/W2135209143","https://openalex.org/W2165108369","https://openalex.org/W2167187514","https://openalex.org/W2189143063","https://openalex.org/W2401977166","https://openalex.org/W2482589566","https://openalex.org/W2618735189","https://openalex.org/W4245048552","https://openalex.org/W6600437753","https://openalex.org/W6633894697","https://openalex.org/W6713412435"],"related_works":["https://openalex.org/W2391533720","https://openalex.org/W2951097643","https://openalex.org/W4309395021","https://openalex.org/W3091989500","https://openalex.org/W3215363805","https://openalex.org/W204133468","https://openalex.org/W2991310128","https://openalex.org/W4307481286","https://openalex.org/W2395174199","https://openalex.org/W2123359227"],"abstract_inverted_index":{"Most":[0],"open-domain":[1],"question":[2,55,143],"answering":[3,144],"systems":[4],"achieve":[5],"better":[6],"performances":[7],"with":[8],"large":[9],"corpora,":[10],"such":[11],"as":[12],"Web,":[13],"by":[14,40],"taking":[15],"advantage":[16],"of":[17,142],"information":[18],"redundancy.":[19],"However,":[20],"explicit":[21],"answers":[22,31,73],"are":[23,32],"not":[24],"always":[25],"mentioned":[26],"in":[27,61,90],"the":[28,75,100,140],"corpus,":[29],"many":[30],"implicitly":[33],"contained":[34],"and":[35,69,106],"can":[36,138],"only":[37],"be":[38],"deducted":[39],"inference.":[41,110],"In":[42],"this":[43],"paper,":[44],"we":[45,78,94,119],"propose":[46],"an":[47,62],"approach":[48],"to":[49,83,88,98,123],"discover":[50],"logical":[51],"knowledge":[52,60,113,126],"for":[53,74,109],"deep":[54],"answering,":[56],"which":[57],"automatically":[58],"extracts":[59],"unsupervised,":[63],"domain-independent":[64],"manner":[65],"from":[66,116],"background":[67],"texts":[68],"reasons":[70],"out":[71],"implicit":[72,101],"questions.":[76],"Firstly,":[77],"use":[79,95,120],"semantic":[80],"role":[81],"labeling":[82],"transform":[84],"natural":[85],"language":[86],"expressions":[87],"predicates":[89,105],"first-order":[91],"logic.":[92],"Then":[93],"association":[96],"analysis":[97],"uncover":[99],"relations":[102],"among":[103],"these":[104,136],"build":[107],"propositions":[108,137],"Since":[111],"our":[112],"is":[114],"drawn":[115],"different":[117],"sources,":[118],"Markov":[121],"logic":[122],"merge":[124],"multiple":[125],"bases":[127],"without":[128],"resolving":[129],"their":[130],"inconsistencies.":[131],"Our":[132],"experiments":[133],"show":[134],"that":[135],"improve":[139],"performance":[141],"significantly.":[145]},"counts_by_year":[{"year":2017,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
