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Knowledge and Information Systems

, Volume 3, Issue 2, pp 168–183 | Cite as

Multipass Algorithms for Mining Association Rules in Text Databases

  • John D. Holt
  • Soon M. Chung
Regular Paper

Abstract.

In this paper, we propose two new algorithms for mining association rules between words in text databases. The characteristics of text databases are quite different from those of retail transaction databases, and existing mining algorithms cannot handle text databases efficiently because of the large number of itemsets (i.e., words) that need to be counted. Two well-known mining algorithms, Apriori algorithm and Direct Hashing and Pruning (DHP) algorithm, are evaluated in the context of mining text databases, and are compared with the new proposed algorithms named Multipass-Apriori (M-Apriori) and Multipass-DHP (M-DHP). It has been shown that the proposed algorithms have better performance for large text databases.

Keywords: Association rules; Data mining; Performance analysis; Text database 

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Copyright information

© Springer-Verlag London Limited 2001

Authors and Affiliations

  • John D. Holt
    • 1
  • Soon M. Chung
    • 1
  1. 1.Department of Computer Science and Engineering, Wright State University, Dayton, Ohio, USAUS

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