Abstract
Wikipedia is the largest online encyclopedia known to date. Its rich content and semi-structured nature has made it into a very valuable research tool used for classification, information extraction, and semantic annotation, among others. Many applications can benefit from the presence of a topic hierarchy in Wikipedia. However, what Wikipedia currently offers is a category graph built through hierarchical category links the semantics of which are un-defined. Because of this lack of semantics, a sub-category in Wikipedia does not necessarily comply with the concept of a sub-category in a hierarchy. Instead, all it signifies is that there is some sort of relationship between the parent category and its sub-category. As a result, traversing the category links of any given category can often result in surprising results. For example, following the category of “Computing” down its sub-category links, the totally unrelated category of “Theology” appears. In this paper, we introduce a novel algorithm that through measuring the semantic relatedness between any given Wikipedia category and nodes in its sub-graph is capable of extracting a category hierarchy containing only nodes that are relevant to the parent category. The algorithm has been evaluated by comparing its output with a gold standard data set. The experimental setup and results are presented.
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© 2013 Springer-Verlag Berlin Heidelberg
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Hejazy, K.A., El-Beltagy, S.R. (2013). An Approach for Deriving Semantically Related Category Hierarchies from Wikipedia Category Graphs. In: Rocha, Á., Correia, A., Wilson, T., Stroetmann, K. (eds) Advances in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol 206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36981-0_8
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DOI: https://doi.org/10.1007/978-3-642-36981-0_8
Publisher Name: Springer, Berlin, Heidelberg
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