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Please use this identifier to cite or link to this item: http://hdl.handle.net/1813/5768
Title: Efficient Keyword Search over Virtual XML Views
Authors: Shao, Feng
Guo, Lin
Botev, Chavdar
Bhaskar, Anand
Chettiah, Muthiah
Yang, Fan
Shanmugasundaram, Jayavel
Keywords: computer science
technical report
Issue Date: 22-Mar-2007
Publisher: Cornell University
Citation: http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cis/TR2007-2077
Abstract: Emerging applications such as personalized portals, enterprise search and web integration systems often require keyword search over semi-structured views. However, traditional information retrieval techniques are likely to be expensive in this context because they rely on the assumption that the set of documents being searched is materialized. In this paper, we present a system architecture and algorithm that can efficiently evaluate keyword search queries over virtual (unmaterialized) XML views. An interesting aspect of our approach is that it exploits indices present on the base data and thereby avoids materializing large parts of the view that are not relevant to the query results. Another feature of the algorithm is that by solely using indices, we can still score the results for queries over the virtual view, and the resulting scores and rank order are the same as if the view was materialized. Our performance evaluation using the INEX data set in the Quark open-source XML database system indicates that the proposed approach is scalable and efficient.
URI: http://hdl.handle.net/1813/5768
Appears in Collections:Computing and Information Science Technical Reports

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