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International Symposium on String Processing and Information Retrieval

SPIRE 2015: String Processing and Information Retrieval pp 1-12 | Cite as

Faster Exact Search Using Document Clustering

  • Jonathan Dimond
  • Peter SandersEmail author
Conference paper
  • 834 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9309)

Abstract

We show how full-text search based on inverted indices can be accelerated by clustering the documents without losing results (SeCluD – Search with Clustered Documents). We develop a fast multilevel clustering algorithm that uses query cost of conjunctive queries as an objective function. Depending on the inputs we get up to four times faster than non-clustered search. The resulting clusters are also useful for data compression and for distributing the work over many machines.

Keywords

Cluster Algorithm Document Cluster Inverted Index Conjunctive Query Cluster Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Karlsruhe Institute of TechnologyKarlsruheGermany

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