Abstract
Processing a twig pattern query in XML document includes structural search and content search. Most existing algorithms only focus on structural search. They treat content nodes the same as element nodes during query processing with structural joins. Due to the high variety of contents, to mix content search and structural search suffers from management problem of contents and low performance. Another disadvantage is to find the actual values asked by a query, they have to rely on the original document. In this paper, we propose a novel algorithm Value Extraction with Relational Table (VERT) to overcome these limitations. The main technique of VERT is introducing relational tables to store document contents instead of treating them as nodes and labeling them. Tables in our algorithm are created based on semantic information of documents. As more semantics is captured, we can further optimize tables and queries to significantly enhance efficiency. Last, we show by experiments that besides solving different content problems, VERT also has superiority in performance of twig pattern query processing compared with existing algorithms.
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Wu, H., Ling, T.W., Chen, B. (2007). VERT: A Semantic Approach for Content Search and Content Extraction in XML Query Processing. In: Parent, C., Schewe, KD., Storey, V.C., Thalheim, B. (eds) Conceptual Modeling - ER 2007. ER 2007. Lecture Notes in Computer Science, vol 4801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75563-0_36
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DOI: https://doi.org/10.1007/978-3-540-75563-0_36
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