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Efficient keyword search over virtual XML views
Author(s) -
Feng Shao,
Guo Lin,
Chavdar Botev,
Bhaskar Anand,
Muthiah M. Muthaia Chettiar,
Fan Yang,
Jayavel Shanmugasundaram
Publication year - 2009
Publication title -
the vldb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.653
H-Index - 90
eISSN - 0949-877X
pISSN - 1066-8888
DOI - 10.1007/s00778-008-0126-x
Subject(s) - computer science , information retrieval , xquery , materialized view , xml , scalability , context (archaeology) , set (abstract data type) , xml database , exploit , database , world wide web , view , programming language , database design , paleontology , biology , computer security
Emerging applications such as personalized portals, enter- prise search and web integration systems often require key- word search over semi-structured views. However, tradi- tional information retrieval techniques are likely to be ex- pensive 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 overvir- tual (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 of queries over the virtual view, and the re- sulting scores are the same as if the view was materialized. Our performance evaluation using the INEX data set in the Quark (5) open-source XML database system indicates that the proposed approach is scalable and efficient.

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