Presents a theoretical rationale for employing a form of information retrieval algorithm that helps searchers better navigate through large document collections by continually revising probability estimates for document subsets. The algorithm avoids assumptions of index term independence and predicts relevance more accurately with increasing…

Discussion of clustering of documents and queries in information retrieval systems focuses on the use of a genetic algorithm to adapt subject descriptions so that documents become more effective in matching relevant queries. Various types of clustering are explained, and simulation experiments used to test the genetic algorithm are described. (27…

Describes the three subsystems of an information retrieval system (document descriptions, queries, and matching algorithms) and argues that the interdependency of these subsystems requires adaptation for the system to perform when any component changes. An algorithm for redescribing documents, in response to changes in queries and retrieval rules,…