Usefulness of Information for Achieving Goals with Disjunctive Premises

Abstract

Abstract We propose a logic-based framework to model a system whose aim is to help provide the user with those pieces of information that are useful with respect to his/her current information need, as well as relevant to his/her query. More precisely, we propose three measures of information usefulness which take into account the fact that the user can be represented as a cognitive agent endowed with some beliefs—a partial “picture” about what it already knows—and goals—a certain state of affairs in which the agent would like to be. This paper extends a previous version of the framework by considering a more realistic hypothesis, according to which there are several ways to achieve goals. We present three different approaches: the binary approach, the ordinal approach, and the numerical approach. We take information retrieval (IR) as a particular application domain, and we compare some existing measures with the usefulness measure we introduce here.