{"id":"https://openalex.org/W73633278","doi":null,"title":"SiteQ: Engineering high performance QA system using lexico-semantic pattern matching and shallow NLP","display_name":"SiteQ: Engineering high performance QA system using lexico-semantic pattern matching and shallow NLP","publication_year":2001,"publication_date":"2001-01-01","ids":{"openalex":"https://openalex.org/W73633278","mag":"73633278"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.11.7129","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.7129","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ai.mit.edu/people/jimmylin/papers/Lee01.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5045508648","display_name":"Gary Geunbae Lee","orcid":"https://orcid.org/0000-0002-3692-6732","observed_orcids":["https://orcid.org/0000-0002-3692-6732","https://orcid.org/0000-0003-4788-0140"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gary Geunbae Lee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101975931","display_name":"Jungyun Seo","orcid":"https://orcid.org/0000-0003-3670-7334","observed_orcids":["https://orcid.org/0000-0003-3670-7334","https://orcid.org/0009-0004-3083-9541"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jungyun Seo","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-3670-7334","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100403754","display_name":"Seungwoo Lee","orcid":"https://orcid.org/0000-0002-2987-150X","observed_orcids":["https://orcid.org/0000-0002-2987-150X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seungwoo Lee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038598860","display_name":"Hanmin Jung","orcid":"https://orcid.org/0000-0001-8690-0664","observed_orcids":["https://orcid.org/0000-0001-8690-0664"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hanmin Jung","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8690-0664","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059634985","display_name":"Bong-Hyun Cho","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bong-Hyun Cho","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073790847","display_name":"Changki Lee","orcid":"https://orcid.org/0000-0001-8373-1500","observed_orcids":["https://orcid.org/0000-0001-8373-1500"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Changki Lee","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8373-1500","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035263900","display_name":"Byung-Kwan Kwak","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Byung-Kwan Kwak","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109869190","display_name":"Jeong-Won Cha","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeong-Won Cha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100745975","display_name":"Dongseok Kim","orcid":"https://orcid.org/0000-0002-9876-3393","observed_orcids":["https://orcid.org/0000-0002-9876-3393"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dongseok Kim","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-9876-3393","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027714787","display_name":"Joohui An","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joohui An","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022865376","display_name":"Harksoo Kim","orcid":"https://orcid.org/0000-0002-8286-7198","observed_orcids":["https://orcid.org/0000-0002-8286-7198"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Harksoo Kim","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-8286-7198","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5007421271","display_name":"Kyungsun Kim","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kyungsun Kim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.1627,"has_fulltext":false,"cited_by_count":86,"citation_normalized_percentile":{"value":0.95655394,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"442","last_page":"451"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.4691999852657318,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.4691999852657318,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.42969998717308044,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10028","display_name":"Topic Modeling","score":0.05609999969601631,"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":0.7979999780654907},{"id":"https://openalex.org/keywords/answer-retrieval","display_name":"answer retrieval","score":0.43700000643730164},{"id":"https://openalex.org/keywords/answer-ranking","display_name":"answer ranking","score":0.4580000042915344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8481976985931396},{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.8349149227142334},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7771860361099243},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6814794540405273},{"id":"https://openalex.org/C121934690","wikidata":"https://www.wikidata.org/wiki/Q1084","display_name":"Noun","level":2,"score":0.5344789028167725},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4993863105773926},{"id":"https://openalex.org/C2780403423","wikidata":"https://www.wikidata.org/wiki/Q6537700","display_name":"Lexical database","level":3,"score":0.464656263589859},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4640594720840454},{"id":"https://openalex.org/C53893814","wikidata":"https://www.wikidata.org/wiki/Q7378909","display_name":"Rule-based machine translation","level":2,"score":0.4267148971557617},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.42417111992836},{"id":"https://openalex.org/C153962237","wikidata":"https://www.wikidata.org/wiki/Q1401131","display_name":"Noun phrase","level":3,"score":0.42096614837646484},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"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}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.11.7129","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.7129","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ai.mit.edu/people/jimmylin/papers/Lee01.pdf","raw_type":"text"},{"id":"mag:73633278","doi":null,"is_oa":false,"landing_page_url":"https://trec.nist.gov/pubs/trec10/papers/SiteQ_trec10.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306421043","display_name":"Text REtrieval Conference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Text REtrieval Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W67698546","https://openalex.org/W1482214997","https://openalex.org/W1511749302","https://openalex.org/W1588490261","https://openalex.org/W1966542308","https://openalex.org/W2028175314","https://openalex.org/W2081580037","https://openalex.org/W2098162425","https://openalex.org/W2421218773","https://openalex.org/W2989499211"],"related_works":["https://openalex.org/W7096362985","https://openalex.org/W7095288925","https://openalex.org/W199895147","https://openalex.org/W7095863643","https://openalex.org/W2593183783","https://openalex.org/W7100656037","https://openalex.org/W7100702718","https://openalex.org/W125965749","https://openalex.org/W7100571053","https://openalex.org/W2593585508"],"abstract_inverted_index":{"this":[0,107],"paper.":[1],"2.":[2],"QA":[3,11,45,85],"track:":[4],"Systems":[5],"and":[6,24,87,115],"Experiences":[7],"In":[8,70],"TRECqo,":[9],"the":[10,18,21,25,32,41,67,73,83,89],"track":[12],"consisted":[13],"of":[14],"three":[15],"separate":[16],"tasks:":[17],"main":[19,33,36],"task,":[20],"list":[22],"task":[23,37,42,90],"context":[26],"task.":[27,34],"We":[28],"participated":[29],"in":[30,43,66],"only":[31],"The":[35,94],"is":[38,77],"similar":[39],"to":[40],"previous":[44,84],"tracks":[46,86],"(TREC-8,":[47],"TREC-9).":[48],"NIST":[49],"provided":[50],"500":[51],"questions":[52,59],"that":[53,71],"seek":[54],"short,":[55],"fact-based":[56],"answers.":[57],"Some":[58],"may":[60],"not":[61],"have":[62],"a":[63],"known":[64],"answer":[65],"document":[68],"collection.":[69],"case,":[72],"response":[74],"string":[75],"\"NIL\"":[76],"judged":[78],"correct.":[79],"This":[80],"differs":[81],"from":[82],"makes":[88],"somewhat":[91],"more":[92,99,117],"difficult.":[93],"answer-string":[95],"should":[96],"contain":[97],"no":[98,116],"than":[100,118],"50":[101],"bytes;":[102],"25o-byte":[103],"runs":[104],"were":[105],"abandoned":[106],"year.":[108],"Participants":[109],"must":[110],"return":[111],"at":[112],"least":[113],"one":[114],"five":[119],"responses":[120],"per":[121],"question":[122],"ranked":[123],"by":[124],"preferences":[125]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":4}],"updated_date":"2026-11-03T10:50:19.383937","created_date":"2016-06-24T00:00:00"}
