Abstract
Search engines have become the most popular tools for finding information on the Internet. A real-world Semantic Web application can benefit from this by combining its features with some features from search engines. In this paper, we describe methods for indexing and searching a populated ontology by using an information retrieval tool; its results are enriched with inference. For visualization purposes, all of the retrieved ontology instances are clustered based on their classes; and the clusters are linked using instance properties. The approach is illustrated using our SWHi (Semantic Web for History) prototype as a case study. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Fahmi, I., Zhang, J., Ellermann, H., & Bouma, G. (2007). SWHi system description: A case study in information retrieval, inference, and visualization in the semantic web. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4519 LNCS, pp. 769–778). Springer Verlag. https://doi.org/10.1007/978-3-540-72667-8_55
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