Contextual data tailoring using ASP

Abstract

In a world of global networking, the variety and abundance of available data generates the need for effectively and efficiently gathering, synthesizing, and querying such data, while reducing information noise. A system where context awareness is integrated with - yet orthogonal to - data management allows the knowledge of the context in which the data are used to better focus on currently useful information (represented as a view), keeping noise at bay. This activity is called context-aware data tailoring. In this paper, after a brief review of the literature on context awareness, we describe a technique for context-aware data tailoring by means of Answer Set Programming (ASP). We use ASP techniques to i) validate the context values against the feasible contexts compatible with a context specification structure called Context Dimension Tree, and ii) convey to the user the context-dependent views associated with the (possibly multiple) current contexts, thus retaining, from the underlying dataset, only the relevant data for each such context. At the same time, ASP allows us to retain the orthogonality of context modeling while adopting the same framework as that of data representation. © 2013 Springer-Verlag Berlin Heidelberg.