Holt, John D.; Chung, Soon M. Multipass algorithms for mining association rules in text databases. (English) Zbl 0991.68629 Knowledge and Information Systems 3, No. 2, 168-183 (2001). 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. Cited in 1 Document MSC: 68U99 Computing methodologies and applications 68P15 Database theory 68P20 Information storage and retrieval of data Keywords:Association rules; Data mining; Performance analysis; Text database PDFBibTeX XML Full Text: DOI