High performance index build algorithms for intranet search engines

  • Authors:
  • Marcus Fontoura;Engene Shekita;Jason Y. Zien;Sridhar Rajagopalan;Andreas Neumann

  • Affiliations:
  • IBM Almaden Research Center, San Jose, CA;IBM Almaden Research Center, San Jose, CA;IBM Almaden Research Center, San Jose, CA;IBM Almaden Research Center, San Jose, CA;IBM Almaden Research Center, San Jose, CA

  • Venue:
  • VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
  • Year:
  • 2004

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Abstract

There has been a substantial amount of research on high-performance algorithms for constructing an inverted text index. However, constructing the inverted index in a intranet search engine is only the final step in a more complicated index build process. Among other things, this process requires an analysis of all the data being indexed to compute measures like PageRank. The time to perform this global analysis step is significant compared to the time to construct the inverted index, yet it has not received much attention in the research literature. In this paper, we describe how the use of slightly outdated information from global analysis and a fast index construction algorithm based on radix sorting can be combined in a novel way to significantly speed up the index build process without sacrificing search quality.