This paper presents results in automated genre classification of digital documents in PDF format. It describes genre classification as an important ingredient in contextualising s...
Abstract. This paper describes an efficient method to construct reliable machine learning applications in peer-to-peer (P2P) networks by building ensemble based meta methods. We co...
In this paper we present a new document representation model based on implicit user feedback obtained from search engine queries. The main objective of this model is to achieve be...
The problem of determining the appropriate number of components is important in finite mixture modeling for pattern classification. This paper considers the application of an unsu...
We use clustering to derive new relations which augment database schema used in automatic generation of predictive features in statistical relational learning. Clustering improves...