Detecting Mismatches between a User's and an Expert's Conceptualisations

The work presented in this paper is part of our ongoing research on applying commonsense reasoning to elicit and maintain models that represent users' conceptualisations. Such user models will enable taking into account the users' perspective of the world and will empower personalisation algorithms for the Semantic Web. A formal approach for detecting mismatches between a user's and an expert's conceptual model is outlined. The formalisation is used as the basis to develop algorithms to compare two conceptualisations defined in OWL. The algorithms are illustrated in a geographical domain using a space ontology developed at NASA, and have been tested by simulating possible user misconceptions

The Role of Deontic Logic in the Specification of Information Systems

In this paper we discuss the role that deontic logic plays in the specification of information systems, either because constraints on the systems directly concern norms or, and even more importantly, system constraints are considered ideal but violable (so-called `soft¿ constraints).\ud To overcome the traditional problems with deontic logic (the so-called paradoxes), we first state the importance of distinguishing between ought-to-be and ought-to-do constraints and next focus on the most severe paradox, the so-called Chisholm paradox, involving contrary-to-duty norms. We present a multi-modal extension of standard deontic logic (SDL) to represent the ought-to-be version of the Chisholm set properly. For the ought-to-do variant we employ a reduction to dynamic logic, and show how the Chisholm set can be treated adequately in this setting. Finally we discuss a way of integrating both ought-to-be and ought-to-do reasoning, enabling one to draw conclusions from ought-to-be constraints to ought-to-do ones, and show by an example the use(fulness) of this

A Description Logic Framework for Commonsense Conceptual Combination Integrating Typicality, Probabilities and Cognitive Heuristics

We propose a nonmonotonic Description Logic of typicality able to account for the phenomenon of concept combination of prototypical concepts. The proposed logic relies on the logic of typicality ALC TR, whose semantics is based on the notion of rational closure, as well as on the distributed semantics of probabilistic Description Logics, and is equipped with a cognitive heuristic used by humans for concept composition. We first extend the logic of typicality ALC TR by typicality inclusions whose intuitive meaning is that "there is probability p about the fact that typical Cs are Ds". As in the distributed semantics, we define different scenarios containing only some typicality inclusions, each one having a suitable probability. We then focus on those scenarios whose probabilities belong to a given and fixed range, and we exploit such scenarios in order to ascribe typical properties to a concept C obtained as the combination of two prototypical concepts. We also show that reasoning in the proposed Description Logic is EXPTIME-complete as for the underlying ALC.Comment: 39 pages, 3 figure