A classification approach to Boolean query reformulation

One of the difficulties in using current Boolean‐based information retrieval systems is that it is hard for a user, especially a novice, to formulate an effective Boolean query. Query reformulation can be even more difficult and complex than formulation since users often have difficulty incorporating the new information gained from the previous search into the next query. In this article, query reformulation is viewed as a classification problem, that is, classifying documents as either relevant or nonrelevant. A new reformulation algorithm is proposed which builds a tree‐structured classifier, called a query tree, at each reformulation from a set of feedback documents retrieved from the previous search. The query tree can easily be transformed into a Boolean query. The query tree is compared to two query reformulation algorithms on benchmark test sets (CACM, CISI, and Medlars). In most experiments, the query tree showed significant improvements in precision over the two algorithms compared in this study. We attribute this improved performance to the ability of the query tree algorithm to select good search terms and to represent the relationships among search terms into a tree structure. © 1997 John Wiley & Sons, Inc.