Aleksander Pivk

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We present a novel approach to learning taxonomic relations between terms by considering multiple and heterogeneous sources of evidence. In order to derive an optimal combination of these sources, we exploit a machine-learning approach , representing all the sources of evidence as first-order features and training standard classifiers. We consider in(More)
The tremendous success of the World Wide Web is countervailed by efforts needed to search and find relevant information. For tabular structures embedded in HTML documents typical keyword or link-analysis based search fails. The Semantic Web relies on annotating resources such as documents by means of ontologies and aims to overcome the bottleneck of finding(More)
Intelligent agents have been applied to electronic commerce, promising a revolution in the way we conduct business, whether business-to-business, business-to-customer or customer-to-customer. This article gives a brief review of agent technologies involved in buying and selling, followed by lists of Internet e-commerce agents. Several agent-mediated(More)