An Automatic Method for WordNet Concept Enrichment using Wikipedia Titles

Knowledge bases such as WordNet are positively utilized for semantic information processing. However, much research indicates that the existing knowledge bases cannot cover all of concepts used in talking and writing in real world. To solve this limitation, this research suggests a method which enri...

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Bibliographic Details
Published inReliable and Autonomous Computational Science pp. 347 - 365
Main Authors Hwang, Myunggwon, Choi, Dongjin, Ko, Byeongkyu, Choi, Junho, Kim, Pankoo
Format Book Chapter
LanguageEnglish
Published Basel Springer Basel 2010
SeriesAutonomic Systems
Subjects
Context Information
Noun Phrase
Proper Noun
Query Answering
Semantic Relation
Online AccessGet full text
ISBN9783034800303
3034800304
DOI10.1007/978-3-0348-0031-0_18

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Summary:Knowledge bases such as WordNet are positively utilized for semantic information processing. However, much research indicates that the existing knowledge bases cannot cover all of concepts used in talking and writing in real world. To solve this limitation, this research suggests a method which enriches WordNet concepts through analyzing Wikipedia document set. Wikipedia currently contains documents more than 3.2 million and it describes tangible and intangible objects in detail. Moreover, it is continuously grown with new subjects and contents by domain-specific specialists. Therefore, the Wikipedia contents can be usefully used for knowledge base enrichment. This paper describes semantic method which conceptualizes titles of Wikipedia documents and which gives a connection between the title concepts and WordNet concepts. Through the experimental result, we could get better precision than that of existing similar method.
ISBN:9783034800303
3034800304
DOI:10.1007/978-3-0348-0031-0_18