Accelerating XML Query Processing on Views

Abstract

With the widespread use of the eXtensible Markup Language (XML), more and more applications store and query XML documents in XML database systems. Thus, how to efficiently process a query and find the specified patterns conforming the query from XML documents is a crucial issue. In this paper, some processing methods are employed on XML documents to improve document retrieval. First, a materialized view is built from an original document for each query. Then, on each materialized view, auxiliary structures such as T-Bitmap and indexes are also built to further accelerate query processing. Finally, four experiments are conducted to show the superiority of the proposed approach.

Author Biographies

Yin-Fu Huang, National Yunlin University of Science and Technology

Yin-Fu Huang received the B.S. degree in computer science from National Chiao-Tung University in 1979, and the M.S. and Ph.D. degrees in computer science from National Tsing-Hua University in 1984 and 1988, respectively. He is currently a Professor in the Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology. Between July 1988 and July 1992, he was with Chung Shan Institute of Science and Technology as an Assistant Researcher. His research interests include database systems, multimedia systems, data mining, mobile computing, and bioinformatics.

Yu-Hsien Cho

Yu-Hsien Cho received his B.S. degree in computer science from Ming Chuan University and M.S. degree in computer sciences from National Yunlin University of Science and Technology in 2012 and 2014, respectively. His major areas of interests are database systems and data mining.

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Authors

  • Yin-Fu Huang National Yunlin University of Science and Technology
  • Yu-Hsien Cho

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Published

06/30/2017

How to Cite

Huang, Y.-F., & Cho, Y.-H. (2017). Accelerating XML Query Processing on Views. Informatica, 41(3). Retrieved from https://www.informatica.si/index.php/informatica/article/view/1200

Issue

Vol. 41 No. 3 (2017)

Section

Regular papers

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