Masumi Shirakawa

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Masumi Shirakawa is an author.


Only those publications related to wikis are shown here.
Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Wikipedia Sets: Context-Oriented Related Entity Acquisition from Multiple Words Data mining
Association thesaurus
Context dependency
WI-IAT English 2011 0 0
Wikipedia sets: Context-oriented related entity acquisition from multiple words Association thesaurus
Context dependency
Data mining
Proceedings - 2011 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2011 English 2011 In this paper, we propose a method which acquires related words (entities) from multiple words by naturally disambiguating their meaning and considering their contexts. In addition, we introduce a bootstrapping method for improving the coverage of association relations. Experimental result shows that our method can acquire related words depending on the contexts of multiple words compared to the ESA-based method. 0 0
Relation extraction between related concepts by combining Wikipedia and web information for Japanese language Natural Language Processing
Lecture Notes in Computer Science English 2010 Construction of a huge scale ontology covering many named entities, domain-specific terms and relations among these concepts is one of the essential technologies in the next generation Web based on semantics. Recently, a number of studies have proposed automated ontology construction methods using the wide coverage of concepts in Wikipedia. However, since they tried to extract formal relations such as is-a and a-part-of relations, generated ontologies have only a narrow coverage of the relations among concepts. In this work, we aim at automated ontology construction with a wide coverage of both concepts and these relations by combining information on the Web with Wikipedia. We propose a relation extraction method which receives pairs of co-related concepts from an association thesaurus extracted from Wikipedia and extracts their relations from the Web. 0 0
Concept vector extraction from Wikipedia category network Wikipedia
Concept vector
Web mining
ICUIMC English 2009 0 0
Wikipedia Mining: Wikipedia as a Corpus por Knowledge Extraction Wikimania English 2008 Wikipedia, a collaborative Wiki-based encyclopedia, has become a huge phenomenon among Internet users. It covers a huge number of concepts of various fields such as Arts, Geography, History, Science, Sports and Games. As a corpus for knowledge extraction, Wikipedia's impressive characteristics are not limited to the scale, but also include the dense link structure, word sense disambiguation based on URL and brief anchor texts. Because of these characteristics, Wikipedia has become a promising corpus and a big frontier for researchers. A considerable number of researches on Wikipedia Mining such as semantic relatedness measurement, bilingual dictionary construction, and ontology construction have been conducted. In this paper, we take a comprehensive, panoramic view of Wikipedia as a Web corpus since almost all previous researches are just exploiting parts of the Wikipedia characteristics. The contribution of this paper is triple-sum. First, we unveil the characteristics of Wikipedia as a corpus for knowledge extraction in detail. In particular, we describe the importance of anchor texts with special emphasis since it is helpful information for both disambiguation and synonym extraction. Second, we introduce some of our Wikipedia mining researches as well as researches conducted by other researches in order to prove the worth of Wikipedia. Finally, we discuss possible directions of Wikipedia research. 0 0