Abstract. We present a novel probabilistic model and specification language for spatial relations. Qualitative spatial logics such as RCC are used for representation and reasoning about physical entities. Our probabilistic RCC semantics enables a more expressive representation of spatial relations. We observe that reasoning in this new framework can be hard. We address this difficulty by using a factored representation based on Markov Random Fields. We formally present the syntax and semantics of a probabilistic RCC. We then use Markov Random Fields to represent our models compactly. Using this representation, we show a basic algorithm for answering queries about the probability of a relation to hold between two entities. Finally, we illustrate the effectiveness of the new approach experimentally over a small set of examples. 1

This paper is mainly concerned with the relation-algebraical aspects of the well-known Region Connection Calculus (RCC). We show that the contact relation algebra (CRA) of certain RCC model is not atomic complete and hence infinite. So in general an extensional composition table for the RCC cannot

dimension as used by the Region Connection Calculus. In this paper we present a canonical model which allows regions and relations between them to be represented as points of the topological space and information about their neighbourhoods. With this formalism we are able to prove that whenever a set

the ontology into an SQL query works only in those cases in which such a compilation, first-order logic (FOL) rewritability, is theoretically possible. Combining lightweight description logics like DL-Lite that are tailored towards FOL-rewritability with spatial calculi like the region connection calculus in a

This paper surveys the work of the qualitative spatial reasoning group at the University of Leeds. The group has developed a number of logical calculi for representing and reasoning with qualitative spatial relations over regions. We motivate the use of regions as the primary spatial entity

We explore the relation--algebraic aspects of the region connection calculus (RCC) of Randell et al. (1992a). In particular, we present a refinement of the RCC8 table which shows that the axioms provide for more relations than are listed in the present table. We also show that each RCC model leads

One of the key strengths of the region connection calculus (RCC) — its generality — is also one of its most important drawbacks for practical applications. The semantics of all the topological relations of the RCC are based on an interpretation of connection between regions. Because of the manner

Abstract. Region Connection Calculus (RCC) is one primary formalism of qualitative spatial reasoning. Standard RCC models are continuous ones where each region is infinitely divisible. This contrasts sharply with the predominant use of finite, discrete models in applications. In a recent paper, Li

Although the region connection calculus (RCC) offers an appealing framework for modelling topological relations, its application in real–world scenarios is hampered when spatial phenomena are affected by vagueness. To cope with this, we present a generalization of the RCC based on fuzzy set theory

The Region-Connection Calculus (RCC) is a well established formal system for qualitative spatial reasoning. It provides an axiomatization of space which takes regions as primitive, rather than as constructions from sets of points. The paper introduces boolean connection algebras (BCAs