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The primary objective of this system is to facilitate knowledge acquisition from documents and aid knowledge discovery through terminology-based similarity calculation and visualization of automatically structured knowledge. This system also supports the integration of different types of databases and simultaneous retrieval of different types of knowledge. In order to accelerate knowledge discovery, we also propose a visualization method for generating similarity-based knowledge maps. The method is based on real-time terminology-based knowledge clustering and categorization and allows users to observe real-time generated knowledge maps, graphically. Lastly, we discuss experiments using the GENIA corpus to assess the practicality and applicability of the system.<\/jats:p>","DOI":"10.1145\/1131348.1131354","type":"journal-article","created":{"date-parts":[[2006,7,25]],"date-time":"2006-07-25T14:14:26Z","timestamp":1153836866000},"page":"74-88","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Terminology-based knowledge mining for new knowledge discovery"],"prefix":"10.1145","volume":"5","author":[{"given":"Hideki","family":"Mima","sequence":"first","affiliation":[{"name":"School of Engineering, University of Tokyo, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sophia","family":"Ananiadou","sequence":"additional","affiliation":[{"name":"School of Informatics, University of Manchester, Manchester, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katsumori","family":"Matsushima","sequence":"additional","affiliation":[{"name":"School of Engineering, University of Tokyo, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2006,3]]},"reference":[{"key":"e_1_2_1_1_1","first-page":"67","article-title":"Automatic terminology management in biomedicine. 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