Towards a belief revision based adaptive and context sensitive information retrieval system

In an adaptive information retrieval (IR) setting, the information seekers' beliefs about which terms are relevant or nonrelevant will naturally fluctuate. This article investigates how the theory of belief revision can be used to model adaptive IR. More specifically, belief revision logic provides a rich representation scheme to formalize retrieval contexts so as to disambiguate vague user queries. In addition, belief revision theory underpins the development of an effective mechanism to revise user profiles in accordance with information seekers' changing information needs. It is argued that information retrieval contexts can be extracted by means of the information-flow text mining method so as to realize a highly autonomous adaptive IR system. The extra bonus of a belief-based IR model is that its retrieval behavior is more predictable and explanatory. Our initial experiments show that the belief-based adaptive IR system is as effective as a classical adaptive IR system. To our best knowledge, this is the first successful implementation and evaluation of a logic-based adaptive IR model which can efficiently process large IR collections

Modelling Information Retrieval Agents with Belief Revision

This paper describes the development and computational testing of a model of the information intermediary based on an AI theory of belief revision. We describe the theoretical foundations of the work in a general account of the way an agent's beliefs and intentions are formed and modified, and in an analysis of the functional tasks an intermediary has to carry out; we indicate the specific developments required to automate and integrate both aspects of intermediary behaviour, as determinants of interactive dialogue with the user; and report, with illustrations, on tests and findings. The research shows that such approaches can be implemented in an essentially principled manner, though there are many large problems still to be overcome, and our experiments are only the first, extremely simple, trials of the basic strategy for intermediary simulation. 1 Introduction We have sought to model the information intermediary by combining a general theory of belief revision, due to Galliers, wi..