Efficient Resource Retrieval from Semantic Knowledge Bases

Efficient resource retrieval is a crucial issue, particularly in the context of Semantic Web, since forms of reasoning are used for answering requests. Resources are retrieved by performing a match test between each resource description and the query. This approach becomes inefficient with the increase of available resources. We propose a method for improving the retrieval process by constructing a tree index through a new conceptual clustering method for resources expressed in Web ontology languages. In the index, the available resource descriptions are located at the leaf nodes, while inner nodes represent intensional descriptions (generalizations) of their child nodes. The match process is executed by following the tree branches whose nodes satisfy the query. Query answering time may be strongly improved as the steps may be O(\log n).

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