Mining and Explaining Relationships in Wikipedia

Xinpeng ZHANG  Yasuhito ASANO  Masatoshi YOSHIKAWA 

Publication
IEICE TRANSACTIONS on Information and Systems  Vol.E95-D  No.7  pp.1918-1931
Publication Date: 2012/07/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Artificial Intelligence, Data Mining
Keyword: 
link analysis,  generalized max-flow,  Wikipedia mining,  relationship, 

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Summary: 
Mining and explaining relationships between concepts are challenging tasks in the field of knowledge search. We propose a new approach for the tasks using disjoint paths formed by links in Wikipedia. Disjoint paths are easy to understand and do not contain redundant information. To achieve this approach, we propose a naive method, as well as a generalized flow based method, and a technique for mining more disjoint paths using the generalized flow based method. We also apply the approach to classification of relationships. Our experiments reveal that the generalized flow based method can mine many disjoint paths important for understanding a relationship, and the classification is effective for explaining relationships.