The Association Rule Mining System for Acquiring Knowledge of DBpedia from Wikipedia Categories

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Wikipedia categories are a useful source of knowledge that is usually expressed in a noun-phrase that contains information about concepts of entities or relations among entities. In DBpedia KBs, they categorize their entities into Wikipedia categories using RDF triples. The RDF triples represent only categories of entities, but not concepts of entities or relations among entities despite the fact that expression of Wikipedia categories contain a wealth of those types of information. In this regard, We propose a method that extracts RDF triples encoding concepts of entities or relations among entities from RDF triples encoding Wikipedia categories of each DBpedia entities using association rule mining techniques that mainly utilize lexical patterns in category expression and a hierarchy of categories. Our extensive experiments show that our approach can mine association rules with more high quality than those of state-of-the-art approaches in this problem.
Publisher
Semantic Web Science Association
Issue Date
2015-10-11
Language
English
Citation

ISWC NLP & DBpedia 2015 Workshop

URI
http://hdl.handle.net/10203/210581
Appears in Collection
CS-Conference Papers(학술회의논문)
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