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…

Discusses information retrieval systems and the need to have them adapt to user needs, integrate information in any format, reveal patterns and trends in information, and answer questions. Topics include statistics and probability; natural language processing; intelligent agents; concept mapping; machine-aided indexing; text mining; filtering;…

Discusses methods of weighting of descriptors in document search patterns together with the concept of relative indexing and conditions which should be satisfied by descriptor weight. A procedure for modifiying document search patterns based on users' informational needs and opinions is outlined, and examples are given. Sixteen references are…