Approximate Query Answering with Knowledge Hierarchy

Approximate Query Answering with Knowledge Hierarchy

Wookey Lee (Inha University, Korea), Myung-Keun Shin (Telecom Business Division, Korea), Soon Young Huh (Korea Advanced Institute of Science and Technology, South Korea), Donghyun Park (Inha University, South Korea) and Jumi Kim (Small Business Institute, Korea)
DOI: 10.4018/978-1-60566-904-5.ch009
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Approximate Query Answering is important for incorporating knowledge abstraction and query relaxation in terms of the categorical and the numerical data. By exploiting the knowledge hierarchy, a novel method is addressed to quantify the semantic distances between the categorical information as well as the numerical data. Regarding that, an efficient query relaxation algorithm is devised to modify the approximate queries to ordinary queries based on the knowledge hierarchy. Then the ranking measures work very efficiently to cope with various combinations of complex queries with respect to the number of nodes in the hierarchy as well as the corresponding cost model.

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