In this paper we are interested in describing Web pages by how users interact within their contents. Thus, an alternate but complementary way of labelling and classifying Web docu...
This paper addresses the challenging problem of learning from multiple annotators whose labeling accuracy (reliability) differs and varies over time. We propose a framework based ...
The Random forest classifier comes to be the working horse for visual recognition community. It predicts the class label of an input data by aggregating the votes of multiple tree...
Abstract. The requirements for effective search and management of the WWW are stronger than ever. Currently Web documents are classified based on their content not taking into acco...
Maria Halkidi, Benjamin Nguyen, Iraklis Varlamis, ...
This paper addresses the problem of fast retrieval of data from XML documents by providing a labeling schema that can easily handle simple as well as complex XPATH queries and als...