: With the increase in the amount and complexity of information, data warehouse performance has become a constant issue, especially for decision support systems. As decisional expe...
Vlad Nicolicin-Georgescu, Vincent Benatier, R&eacu...
The proliferation of knowledge-sharing communities and the advances in information extraction have enabled the construction of large knowledge bases using the RDF data model to re...
Nicoleta Preda, Gjergji Kasneci, Fabian M. Suchane...
Current Data Mining techniques usually do not have a mechanism to automatically infer semantic features inherent in the data being “mined”. The semantics are either injected i...
Our research aims at interactive document viewers that can select and highlight relevant text passages on demand. Another related objective is the generation of topic-specific su...
The discovery of sequential patterns, which extends beyond frequent item-set finding of association rule mining, has become a challenging task due to its complexity. Essentially, ...
Hermes is an ontology-based framework for building news personalization services. This framework consists of a news classification phase, which classifies the news, a knowledge ...
Kim Schouten, Philip Ruijgrok, Jethro Borsje, Flav...
Abstract. The maintenance of large knowledge systems usually is a rather complex task. In this paper we will show that extensions or modifications of a knowledge base can be suppo...
Dietmar Seipel, Joachim Baumeister, Marbod Hopfner
Selection of Commercial-off-The-Shelf (COTS) software products is a knowledge-intensive process. In this paper, we show how knowledge bases can be used to facilitate the COTS selec...
We present a framework for expressing different merging operators for belief sets. This framework is a generalisation of our earlier work concerning consistency-based belief revisi...
Abstract. This paper describes the new e-learning tool CHESt that allows students to search in a knowledge base for short (teaching) multimedia clips by using a semantic search eng...