A General and Efficient Approach for Solving Nearest Neighbor Problem in the Vague Query System

This article presents a general and efficient approach for finding the best match for complex vague queries in the Vague Query System (VQS) [16]. The VQS is an extension to conventional database systems and can operate on top of them in order to facilitate vague retrieval capabilities. The VQS's key is Numeric-Coordinate-Representation-Tables (NCR-Tables), which store semantic background information of attributes. Concretely, attributes of arbitrary types in a query relation/view are mapped to the Euclidean space and kept by NCR-Tables. Answering a complex vague query requires parallel searching on some NCR-Tables, which usually contain multidimensional data. In [17] Kueng et al proposed an incremental hyper-cube approach for solving complex vague queries, however, this approach has weaknesses lead to degenerate the search performance of the VQS. Theoretical analyses and experimental results in this article will prove that our new approach defeats all these defects and makes the VQS a full-fledged flexible query answering system.