4 research outputs found

    Rewriting xpath queries using materialized views

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    As a simple XML query language but with enough expressive power, XPath has become very popular. To expedite evaluation of XPath queries, we consider the problem of rewriting XPath queries using materialized XPath views. This problem is very important and arises not only from query optimization in server side but also from semantic caching in client side. We consider the problem of deciding whether there exists a rewriting of a query using XPath views and the problem of finding minimal rewritings. We first consider those two problems for a very practical XPath fragment containing the descendent, child, wildcard and branch features. We show that the rewriting existence problem is coNP-hard and the problem of finding minimal rewritings is Σ p 3. We also consider those two rewriting problems for three subclasses of this XPath fragment, each of which contains child feature and two of descendent, wildcard and branch features, and show that both rewriting problems can be polynomially solved. Finally, we give an algorithm for finding minimal rewritings, which is sound for the XPath fragment, but is also complete and runs in polynomial time for its three subclasses.

    Topic-Centric Querying of Web Information Resources

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    This paper deals with the problem of modeling web information resources using expert knowledge and personalized user information, and querying them in terms of topics and topic relationships. We propose a model for web information resources, and a query language SQL-TC (Topic-Centric SQL) to query the model. The model is composed of web-based information resources (XML or HTML documents on the web), expert advice repositories (domain-expertspecified metadata for information resources), and personalized information about users (captured as user profiles, that indicate users' preferences as to which expert advice they would like to follow, and which to ignore, etc). The query language SQL-TC makes use of the metadata information provided in expert advice repositories and embedded in information resources, and employs user preferences to further refine the query output. Query output objects/tuples are ranked with respect to the (expert-judged and user-preference-revised) importance values of requested topics/metalinks, and the query output is limited by either top n-ranked objects/tuples, or objects/tuples with importance values above a given threshold, or both.
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