Incorporating different search models into one document retrieval system

Abstract

Many effective search strategies derived from different models are available for document retrieval systems. However, it does not appear that there is a single most effective strategy. Instead, different strategies perform optimally under different conditions. This paper outlines the design of an adaptive document retrieval system that chooses the best search strategy for a particular situation and user. In order to be able to support a variety of search strategies, a general network representation of the documents and terms in the database is proposed. This network representation leads to efficient methods of generating and using document and term classifications.One of the most desirable features of an adaptive system would be the ability to learn from experience. A method of incorporating this learning ability into the system is described. The adaptive control strategy for choosing search strategies enables the system to base its actions on a number of factors, including a model of the current user.Finally, some ideas for a flexible interface for casual users are suggested. Part of this interface is the heuristic search, which is used when searches based on formal models have failed. The heuristic search provides a browsing capability for the user.