Browsing by Author "LIN, Chunbin"

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    Effective XML Keyword Search with Nearest Common Object Node Semantics
    (2012-09-20) LE, Thuy Ngoc; LING, Tok Wang; LIN, Chunbin; LU, Jiaheng
    Lowest Common Ancestor (LCA) semantics and its extensions such as SLCA, MLCA, VLCA and ELCA. However, these approaches commonly do not return a complete answer set for a query because they can only find the common ancestors of a set of keywords but cannot find their common information appearing at their descendants in an XML document. In this paper, we introduce a new semantics, called Nearest Common Objects Node (NCON), which guarantees that both common ancestors and common descendants are included in the answer set for a query and therefore enables us to answer a query more completely. We also propose an NCON-based approach for XML keyword search, which exploits not only the index of the original XML document, but also the index of its reversed XML document, and devise optimization techniques to facilitate the process of finding NCONs. We have developed XComplete, a system for our NCON-based approach, which essentially uses the NCON semantics and post-processing techniques, altogether enable XComplete to return an answer set with completeness, meaningfulness, no irrelevance, no duplicate and comprehension to users. The results of our extensive experiments show that our proposed approach outperforms the existing LCA-based approaches in terms of both effectiveness and efficiency.
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    Object Semantics for XML Keyword Search
    (2013-05-21T01:18:54Z) LE, Thuy Ngoc; LING, Tok Wang; JAGADISH, H. V.; LIN, Chunbin; LU, Jiaheng
    We know that some XML elements correspond to objects (in the sense of object-orientation) and others do not. The question we consider in this paper is what benefits we can derive from paying attention to such object semantics, particularly for the problem of keyword queries. Keyword queries against XML data have been studied extensively in recent years, with several lowest-common-ancestor based schemes proposed for this purpose, including SLCA, MLCA, VLCA, and ELCA. It is easy to see that identifying objects can help each of these techniques return more meaningful answers than just the LCA node (or subtree). It is more interesting to see that object semantics can also be used to benefit the search itself. For this purpose, we introduce a novel nearest common object node semantics (NCON), which includes not just common ancestors but also common descendants and referenced objects in evaluating a query. We have developed XComplete, a system for our NCON-based approach, and used it in our extensive experimental evaluation. The experimental results show that our proposed approach outperforms the existing LCA-based approaches in terms of both effectiveness and efficiency.