Typical text clustering methods use the bag of words (BoW) representation to describe content of documents. However, this method is known to have several limitations. Employing Wikipedia as the lexical knowledge base has shown an improvement of the text representation for data-mining purposes. Promising extensions of that trend employ hierarchical organization of Wikipedia category system. In this paper we propose three path-based measures for calcu- lating document relatedness in such conceptual space and compare them with the Path Length widely used approach. We perform their evaluation using the OPTICS clustering algorithm for categorization of keyword-based search results. The results have shown that our method outperforms the Path-Length approach.
Authors
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1007/978-3-319-08326-1_44
- Category
- Aktywność konferencyjna
- Type
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language
- angielski
- Publication year
- 2014
