In this paper we introduce the TTCSE , a linguistic resource that relies on BabelNet, NASARI and ConceptNet, that has now been used to compute the conceptual similarity between concept pairs. The conceptual representation herein provides uniform access to concepts based on BabelNet synset IDs, and consists of a vectorbased semantic representation which is compliant with the Conceptual Spaces, a...

Our project concerns anonymity, that is the ability of users in a system to transmit information without revealing their own identities. There are a number of protocols claiming to guarantee users’ anonymity in different situations, but there is no clear way to compare these protocols in terms of how anonymous their users really are. In order to develop a measure of anonymity, we need to be abl...

Some important research problems within reasoning about beliefs are how to deal with incomplete, inaccurate or uncertain beliefs, when to ascribe beliefs and how to make reasoning about beliefs more common-sensical. We present two systems that attack such problems. The first, called CaseMent, uses case-based reasoning to reason about beliefs. It appears that using cases as opposed to roles has ...

Emotions play a key role in natural language understanding and sensemaking. Pure machine learning usually fails to recognize and interpret emotions in text. The need for knowledge bases that give access to semantics and sentics (the conceptual and affective information) associated with natural language is growing exponentially in the context of big social data analysis. To this end, this paper ...

Despite the current belief that much common sense reasoning is nonmonotonic in nature, research indicates that only a limited percentage of people are good at nonmonotonic reasoning. Good nonmonotonic reasoners recognize the logical strengths and weaknesses of some arguments. In the present study, we focus on differences in the probabilistic interpretation of the modifiers typically and usually...

We present extended conceptual logic programs (ECLPs), for which reasoning is decidable and, moreover, can be reduced to finite answer set programming. ECLPs are useful to reason with both ontological and rule-based knowledge, which is illustrated by simulating reasoning in an expressive description logic (DL) equipped with DL-safe rules. Furthermore, ECLPs are more expressive in the sense that...

We present extended conceptual logic programs (ECLPs), for which reasoning is decidable and, moreover, can be reduced to finite answer set programming. ECLPs are useful to reason with both ontological and rule-based knowledge, which is illustrated by simulating reasoning in an expressive description logic (DL) equipped with DL-safe rules. Furthermore, ECLPs are more expressive in the sense that...

Common-sense reasoning is important for AI applications, both in NLP and many vision and robotics tasks. We propose NaturalLI: a Natural Logic inference system for inferring common sense facts – for instance, that cats have tails or tomatoes are round – from a very large database of known facts. In addition to being able to provide strictly valid derivations, the system is also able to produce ...

Qualitative Reasoning captures human common sense understanding of the behavior of real world physical systems. Qualitative models use a rich explicit conceptual vocabulary and therefore a qualitative simulation provides an explanation as well as a description of the system’s behavior. These properties make Qualitative Reasoning suitable for use in several application fields like education and ...

This special issue consists largely of expanded and revised versions of selected papers of the Fifth International Symposium on Logical Formalizations of Commonsense Reasoning (Common Sense 2001), held at New York University in May 2001.1,2 The Common Sense Symposia, first organized in 1991 by John McCarthy and held roughly biannually since, are dedicated to exploring the development of formal ...