Description Logics (DLs) are knowledge representation languages useful to represent concepts and roles. Fuzzy Description Logics (FDLs) incorporate both vague concepts and vague roles modeling them as fuzzy sets and fuzzy relations respectively. In the present paper, following ideas from Hájek, we propose the use of t-norm based (fuzzy) logics with truth constants in the language as logics unde...

Topological integrity constraints control the topological properties of spatial objects and the validity of their topological relationships in spatial databases. These constraints can be specified by using formal languages such as the spatial extension of the Object Constraint Language (OCL). Spatial OCL allows the expression of topological constraints involving crisp spatial objects. However, ...

This paper asks why information should ever be expressed vaguely, reassessing some previously proposed answers to this question and suggesting some new ones. Particular attention is paid to the benefits that vague expressions can have in situations where agreement over the meaning of an expression cannot be taken for granted. A distinction between two different versions of the above-mentioned q...

The paradigm of deterministic nite-state automata (DFAs) and their corresponding regular languages have been shown to be very useful for addressing fundamental issues in recurrent neural networks. The issues that have been addressed include knowledge representation, extraction, and reenement as well development of advanced learning algorithms. Recurrent neural networks are also very promising t...

This paper examines the role of gradable properties in referring expressions, from a perspective of natural language generation. Firstly, we propose a simple semantic analysis of vague descriptions (i.e., referring expressions that contain gradable adjectives) that reflects the context-dependent meaning of the adjectives in them. Secondly, we show how this type of analysis can inform algorithms...

This paper introduces a semantic model for vague quantifiers (VQs) combining Fuzzy Theory (FT) and Supervaluation Theory (ST), which are the two main theories on vagueness, a common source of uncertainty in natural language. After comparing FT and ST, I will develop the desired model and a numerical method for evaluating truth values of vague quantified statements, called the Modified Glöckner’...