A Study for Knowledge ExtractionAid System from Web Text

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We aimed at a system that extracts texts or part of texts including knowledge which various users are interested in from huge amount of Web pages in this research. We developed the following systems for this purpose.(1) A system which extracts terms that characterize a search engine result web pages using the term extraction system "Gensen Web" which we have already developed.(2) A system which extracts definition of terms which we extract by the system of (1) and relations among these terms. To accomplish this task, we utilize the usage consultation system via Web search engine called "Kiwi."(3) In order to make more efficient system of (2), we employed a suffix array technology and use the web pages crawled in advance. We named the system as "UT-Kiwi" and made it publically available from the Internet.(4) To enhance the above described systems, we developed a people name search engine named "Nayose." When we search pages for given people name, we get pages indicating distinct person even though they have the same name. Our system clusters those web pages according to the real person.(5) Aiming at more innovative knowledge extraction, we also studied new machine learning algorithms based on non-parametric Bayes theory.(6) Utilize web page in English more, we developed the Sakumon system which is an assisting system for English cloze test using English web pages.