BitCube: A Three-Dimensional Bitmap Indexing for XML Documents

  • Authors:

  • Jong P. Yoon;Vijay Raghavan;Venu Chakilam;Larry Kerschberg

  • Affiliations:

  • Center for Advanced Computer Studies, University of Louisiana, Lafayette, LA 70504-4330, USA. jyoon@cacs.louisiana.edu;Center for Advanced Computer Studies, University of Louisiana, Lafayette, LA 70504-4330, USA. raghavan@cacs.louisiana.edu;Center for Advanced Computer Studies, University of Louisiana, Lafayette, LA 70504-4330, USA. vmc0583@cacs.louisiana.edu;E-Center for E-Business and Department of Information and Software Engineering, George Mason University, Fairfax, VA 22030-4444, USA. kersch@gmu.edu

  • Venue:
  • Journal of Intelligent Information Systems
  • Year:
  • 2001

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Abstract

XML is a new standard for exchanging and representing information on the Internet. Documents can be hierarchically represented by XML-elements. In this paper, we propose that an XML document collection be represented and indexed using a bitmap indexing technique. We define the similarity and popularity operations suitable for bitmap indexes. We also define statistical measurements in the BitCube: center, and radius. Based on these measurements, we describe a new bitmap indexing based technique to cluster XML documents. The techniques for clustering are motivated by the fact that the bitmap indexes are expected to be very sparse.Furthermore, a 2-dimensional bitmap index is extended to a 3-dimensional bitmap index, called the BitCube. Sophisticated querying of XML document collections can be performed using primitive operations such as slice, project, and dice. Experiments show that the BitCube can be created efficiently and the primitive operations can be performed more efficiently with the BitCube than with other alternatives.