Abstract
Evaluation of keyword queries over XML documents is one of the most fundamental tasks for XML data management. Previous methods have focused on the processing of deterministic XML data. However, uncertain data are inherent in practical applications, and how to support efficient keyword search over fuzzy XML data remains at large an open problem. In this paper, we tackle the problem of efficiently producing SLCA (smallest lowest common ancestor) results for keyword queries in fuzzy XML documents. We propose an efficient approach that can find all SLCA results for a given keyword query over fuzzy XML data. In particular, we introduce an effective method to transform a simple keyword query into a segmented keyword query that captures the original query requirements and conforms to the underlying fuzzy XML data. The proposed approach could help us eliminate irrelevant SLCA results and speed up the query processing. The final experiments show the effectiveness and efficiency of our proposed approach in generating SLCA results.
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