Relation extraction between related concepts by combining Wikipedia and web information for Japanese language
|Relation extraction between related concepts by combining Wikipedia and web information for Japanese language|
|Author(s)||Shirakawa M., Nakayama K., Aramaki E., Hara T., Nishio S.|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||natural language processing, ontology, thesaurus (Extra: Domain specific, Named entities, NAtural language processing, Ontology construction, Relation extraction, Web based, Web information, Wikipedia, Computational linguistics, Information retrieval, Infrared devices, Natural language processing systems, Semantic Web, Semantics, Thesauri, Ontology)|
|Article||BASE, CiteSeerX, Google Scholar|
|Web||Ask, Bing, Google (PDF), Yahoo!|
|Download and mirrors|
|Local copy||Not available|
|Remote mirror(s)||Not available|
|Export and share|
|BibTeX, CSV, RDF, JSON|
|Browse properties · List of conference papers|
Relation extraction between related concepts by combining Wikipedia and web information for Japanese language is a 2010 conference paper written in English by Shirakawa M., Nakayama K., Aramaki E., Hara T., Nishio S. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
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.
- This section requires expansion. Please, help!
Probably, this publication is cited by others, but there are no articles available for them in WikiPapers.