{"id":"https://openalex.org/W2750782808","doi":"https://doi.org/10.1109/jcsse.2017.8025918","title":"A semantic approach for question answering using DBpedia and WordNet","display_name":"A semantic approach for question answering using DBpedia and WordNet","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2750782808","doi":"https://doi.org/10.1109/jcsse.2017.8025918","mag":"2750782808"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/jcsse.2017.8025918","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5074890681","display_name":"Kittiphong Sengloiluean","orcid":null},"institutions":[{"id":"https://openalex.org/I179193067","display_name":"Khon Kaen University","ror":"https://ror.org/03cq4gr50","country_code":"TH","type":"education","lineage":["https://openalex.org/I179193067"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Kittiphong Sengloiluean","raw_affiliation_strings":["Department of Computer Science, KhonKaen University, KhonKaen, Thailand"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, KhonKaen University, KhonKaen, Thailand","institution_ids":["https://openalex.org/I179193067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024438652","display_name":"Ngamnij Arch\u2010int","orcid":"https://orcid.org/0000-0003-1948-4183"},"institutions":[{"id":"https://openalex.org/I179193067","display_name":"Khon Kaen University","ror":"https://ror.org/03cq4gr50","country_code":"TH","type":"education","lineage":["https://openalex.org/I179193067"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Ngamnij Arch-int","raw_affiliation_strings":["Khon Kaen University, Khon Kaen, TH"],"affiliations":[{"raw_affiliation_string":"Khon Kaen University, Khon Kaen, TH","institution_ids":["https://openalex.org/I179193067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103271801","display_name":"Somjit Arch\u2010int","orcid":"https://orcid.org/0000-0002-1684-5409"},"institutions":[{"id":"https://openalex.org/I179193067","display_name":"Khon Kaen University","ror":"https://ror.org/03cq4gr50","country_code":"TH","type":"education","lineage":["https://openalex.org/I179193067"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Somjit Arch-int","raw_affiliation_strings":["Department of Computer Science, KhonKaen University, KhonKaen, Thailand"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, KhonKaen University, KhonKaen, Thailand","institution_ids":["https://openalex.org/I179193067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009400451","display_name":"Theerayut Thongkrau","orcid":"https://orcid.org/0000-0002-6210-8573"},"institutions":[{"id":"https://openalex.org/I179193067","display_name":"Khon Kaen University","ror":"https://ror.org/03cq4gr50","country_code":"TH","type":"education","lineage":["https://openalex.org/I179193067"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Theerayut Thongkrau","raw_affiliation_strings":["Department of Computer Science, KhonKaen University, KhonKaen, Thailand"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, KhonKaen University, KhonKaen, Thailand","institution_ids":["https://openalex.org/I179193067"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.15,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":4,"citation_normalized_percentile":{"value":0.435396,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":77,"max":79},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998,"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":0.9998,"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":0.9993,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9921,"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":[],"concepts":[{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.9227724},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.91638315},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.85086596},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6897117},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.56430316},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.51229775},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.48947012},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4704465},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.45409885},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.43856964},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.42833406},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.09162927},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06705153},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/jcsse.2017.8025918","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.74,"id":"https://metadata.un.org/sdg/4","display_name":"Quality education"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":21,"referenced_works":["https://openalex.org/W1842073304","https://openalex.org/W1975836659","https://openalex.org/W1980901184","https://openalex.org/W1985640802","https://openalex.org/W1986641982","https://openalex.org/W1992712260","https://openalex.org/W2026810221","https://openalex.org/W2039345667","https://openalex.org/W2054070929","https://openalex.org/W2081580037","https://openalex.org/W2086458382","https://openalex.org/W2091361863","https://openalex.org/W2123442489","https://openalex.org/W2136480620","https://openalex.org/W2188053670","https://openalex.org/W2205441555","https://openalex.org/W2278131208","https://openalex.org/W2467134778","https://openalex.org/W2962777755","https://openalex.org/W341485587","https://openalex.org/W632432350"],"related_works":["https://openalex.org/W4319432032","https://openalex.org/W2957377172","https://openalex.org/W2907883452","https://openalex.org/W2569513598","https://openalex.org/W2165693052","https://openalex.org/W2164877079","https://openalex.org/W2113471940","https://openalex.org/W2047143235","https://openalex.org/W2043952800","https://openalex.org/W101928771"],"abstract_inverted_index":{"Semantic":[0],"Question":[1],"Answering":[2],"(SQA)":[3],"was":[4,16,44,64],"concerned":[5],"about":[6],"the":[7,20,24,27,33,40,51,60,91,95,106,110,121,125,134,138,145],"natural":[8,28],"language":[9,29],"processing.":[10],"The":[11],"purpose":[12],"of":[13,53,59,100,112,114,127,129,137,140,158,163,169],"this":[14,47,75,89],"study":[15,76],"to":[17,22,31],"help":[18],"facilitate":[19],"users":[21],"access":[23],"information":[25],"through":[26],"and":[30,35,55,86,108,123,131,153,165],"obtain":[32],"concise":[34],"needed":[36],"information.":[37],"As":[38],"considered":[39],"current":[41],"studies,":[42],"it":[43],"found":[45],"that":[46],"processing":[48,68],"still":[49],"encountered":[50],"problems":[52,96,111,126],"flexibility":[54],"accuracy,":[56],"particularly":[57],"those":[58],"question":[61,71,82,107,122,150],"processing,":[62],"which":[63],"a":[65,78],"very":[66],"important":[67],"for":[69,81,93],"developing":[70],"answering":[72,83],"system.":[73],"Thus,":[74],"proposed":[77,98],"semantic":[79],"approach":[80,143],"using":[84],"DBpedia":[85,152],"WordNet.":[87],"For":[88],"paper,":[90],"techniques":[92],"solving":[94,109,124],"were":[97],"consisting":[99],"(1)":[101],"extracting":[102,118],"named":[103,115],"entities":[104],"from":[105,120,148],"similarities":[113,128],"entities,":[116],"(2)":[117],"properties":[119],"properties,":[130],"(3)":[132],"evaluating":[133],"accurate":[135],"capability":[136],"answer":[139],"question.":[141],"This":[142],"evaluated":[144],"test":[146],"dataset":[147],"TREC":[149],"collections,":[151],"achieved":[154],"an":[155,160,166],"F-measure":[156],"score":[157],"93.43%,":[159],"average":[161,167],"precision":[162],"92.73%,":[164],"recall":[168],"94.15%":[170],"over":[171],"500":[172],"questions.":[173]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2750782808","counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-01-16T17:50:52.758811","created_date":"2017-09-15"}