DC Field | Value | Language |
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dc.contributor.author | Jung, H | - |
dc.contributor.author | Yi, E | - |
dc.contributor.author | Kim, D | - |
dc.contributor.author | Lee, GG | - |
dc.date.accessioned | 2016-04-01T02:19:22Z | - |
dc.date.available | 2016-04-01T02:19:22Z | - |
dc.date.created | 2009-03-18 | - |
dc.date.issued | 2005-03 | - |
dc.identifier.issn | 0306-4573 | - |
dc.identifier.other | 2004-OAK-0000004695 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/24911 | - |
dc.description.abstract | POSIE (POSTECH Information Extraction System) is an information extraction system which uses multiple learning strategies, i.e., SmL, user-oriented learning, and separate-context learning, in a question answering framework. POSIE replaces laborious annotation with automatic instance extraction by the SmL from structured Web documents, and places the user at the end of the user-oriented learning cycle. Information extraction as question answering simplifies the extraction procedures for a set of slots. We introduce the techniques verified on the question answering framework, such as domain knowledge and instance rules, into an information extraction problem. To incrementally improve extraction performance, a sequence of the user-oriented learning and the separate-context learning produces context rules and generalizes them in both the learning and extraction phases. Experiments on the "continuing education" domain initially show that the F1-measure becomes 0.477 and recall 0.748 with no user training. However, as the size of the training documents grows, the F1-measure reaches beyond 0.75 with recall 0.772. We also obtain F-measure of about 0.9 for five out of seven slots on "job offering" domain. (C) 2003 Elsevier Ltd. All rights reserved. | - |
dc.description.statementofresponsibility | X | - |
dc.language | English | - |
dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | - |
dc.relation.isPartOf | INFORMATION PROCESSING & MANAGEMENT | - |
dc.subject | information extraction | - |
dc.subject | question answering | - |
dc.subject | user-oriented learning | - |
dc.subject | lexico-semantic pattern | - |
dc.subject | machine learning | - |
dc.title | Information extraction with automatic knowledge expansion | - |
dc.type | Article | - |
dc.contributor.college | 컴퓨터공학과 | - |
dc.identifier.doi | 10.1016/S0306-4573(03)00066-9 | - |
dc.author.google | Jung, H | - |
dc.author.google | Yi, E | - |
dc.author.google | Kim, D | - |
dc.author.google | Lee, GG | - |
dc.relation.volume | 41 | - |
dc.relation.issue | 2 | - |
dc.relation.startpage | 217 | - |
dc.relation.lastpage | 242 | - |
dc.contributor.id | 10103841 | - |
dc.relation.journal | INFORMATION PROCESSING & MANAGEMENT | - |
dc.relation.index | SCI급, SCOPUS 등재논문 | - |
dc.relation.sci | SCIE | - |
dc.collections.name | Journal Papers | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | INFORMATION PROCESSING & MANAGEMENT, v.41, no.2, pp.217 - 242 | - |
dc.identifier.wosid | 000225323100004 | - |
dc.date.tcdate | 2019-02-01 | - |
dc.citation.endPage | 242 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 217 | - |
dc.citation.title | INFORMATION PROCESSING & MANAGEMENT | - |
dc.citation.volume | 41 | - |
dc.contributor.affiliatedAuthor | Lee, GG | - |
dc.identifier.scopusid | 2-s2.0-7544242036 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.wostc | 5 | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | information extraction | - |
dc.subject.keywordAuthor | question answering | - |
dc.subject.keywordAuthor | user-oriented learning | - |
dc.subject.keywordAuthor | lexico-semantic pattern | - |
dc.subject.keywordAuthor | machine learning | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Information Science & Library Science | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Information Science & Library Science | - |
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