Abstract
SEWEBAR is a research project the goal of which is to study possibilities of dissemination of analytical reports through Semantic Web. We are interested in analytical reports presenting results of data mining. Each analytical report gives answer to one analytical question. Lot of interesting analytical questions can be answered by GUHA procedures implemented in the LISp-Miner system. The SEWEBAR project deals with these analytical questions. However the process of formulating and answering such analytical questions requires various background knowledge. The paper presents first steps in storing and application of several forms of background knowledge in the SEWEBAR project. Examples concerning dealing with medical knowledge are presented.
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Rauch, J., Šimůnek, M. (2009). Dealing with Background Knowledge in the SEWEBAR Project. In: Berendt, B., et al. Knowledge Discovery Enhanced with Semantic and Social Information. Studies in Computational Intelligence, vol 220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01891-6_6
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DOI: https://doi.org/10.1007/978-3-642-01891-6_6
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