The Semantic Web search aims to overcome the bottleneck of finding relevant information using formal knowledge models, e.g. ontologies. The focus of this paper is to extend a typical search engine with semantic search over tabular structures. We categorize HTML documents into topics and genres. Using the TARTAR system, tabular structures in the documents are then automatically transformed into ontologies and annotated to build a knowledge base. When posting queries, users receive responses not just as lists of links and description extracts, but also enhanced with replies in the form of detailed structured data. Povzetek:
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