In this paper, we focus on the problem of effectively and efficiently answering XML keyword search. We first show the weakness of existing SLCA (Smallest Lowest Common Ancestor) based solutions, and then we propose the concept of Candidate Fragment. ACandidate Fragment is a meaningful sub tree in the XML document tree, which has the appropriate granularity. To efficiently compute Candidate Fragments as the answers of XML keyword search, we design Node Match Algorithm and Path Match algorithm. Finally, we conduct extensive experiments to show that our approach is both effective and efficient.
CITATION STYLE
Wen, Y., Zhang, H., Zhang, Y., Zhang, L., Xu, L., & Yuan, X. (2011). Effective keyword search for candidate fragments of xml documents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6637 LNCS, pp. 427–439). Springer Verlag. https://doi.org/10.1007/978-3-642-20244-5_41
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