Both document clustering and word clustering are well studied problems. Most existing algorithms cluster documents and words separately but not simultaneously. In this paper we pr...
We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
Abstract. This paper shows how Wikipedia and the semantic knowledge it contains can be exploited for document clustering. We first create a concept-based document representation b...
Anna Huang, David N. Milne, Eibe Frank, Ian H. Wit...
A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an e...
This article explicitly outlines an approach designed to allow optimal utilisation of Analytics in the industry setting. The paper focuses on the key stages of the Analytics proce...