Fuzzy logic based methods have been widely used in linguistic modeling [6]. Here we use a different framework of random set to interpret imprecise concepts. This framework is referred to as label semantics [8]. Within this framework, fuzzy concepts are modeled by quantifying the subjective uncertainty associated with whether or not a label expression is appropriate to describe a particular valu...

The notion that a text is coherent in virtue of the relations which hold between the elements of that text has become fairly common currency both in the study of discourse coherence and in the eld of text generation The set of relations proposed in Rhetorical Structure Theory Mann and Thompson has had particular in uence in both of these elds But the widespread adoption of relational terminolog...

It is often argued that a set of standard linguistic processing functionalities should be identified, with each of them given a formal specification. We would benefit from the formal specifications; for example, the semi-automated composition of a complex language processing workflow could be enabled in due time. This paper extracts a standard set of linguistic processing functionalities and tr...

Term extraction is an essential task in domain knowledge acquisition. We propose two new measures to extract multiword terms from a domain-specific text. The first measure is both linguistic and statistical based. The second measure is graph-based, allowing assessment of the importance of a multiword term of a domain. Existing measures often solve some problems related (but not completely) to t...

We propose a computational model of situated language comprehension based on the Indexical Hypothesis that generates meaning representations by translating amodal linguistic symbols to modal representations of beliefs, knowledge, and experience external to the linguistic system. This Indexical Model incorporates multiple information sources, including perceptions, domain knowledge, and short-te...

1. I n t r o d u c t i o n R o u g h l y speak ing , a fuzzy set is a class w i t h u n s h a r p b o u n d a r i e s , tha t is, a class in w h i c h the t r ans i t i on f rom m e m b e r s h i p t o n o n m e m b e r s h i p is g r a d u a l r a the r t h a n a b r u p t . In this sense , t h e class of ta l l m e n is a fuzzy set , as are t he classes o f beaut i fu l w o m e n , y o u n g ...

With the increasing number of ontologies available on the web, the problem of merging ontologies from different sources to interoperate applications becomes important. This paper presents a novel approach for merging of light-weight ontologies based on answer set programming (ASP) and linguistic background knowledge. ASP provides a declarative execution environment for intuitive merging rules. ...

The proposed solution for authorship attribution combines a couple of the most important features identified in previous research in this domain with classification algorithms in order to detect the correct author. We consider that the most relevant aspect of our work is the small number of linguistic features and the use of the same framework to solve both the open and the closed class authors...

The notion that a text is coherent in virtue of the `relations' which hold between the elements of that text has become fairly common currency, both in the study of discourse coherence and in the eld of text generation. The set of relations proposed in Rhetorical Structure Theory (Mann and Thompson [14]) has had particular in uence in both of these elds. But the widespread adoption of `relation...

Any computing with words (CW) system is required to assign a phrase in natural language to the fuzzy values it provides as its output. This paper explores different linguistic approximation methods for CW systems. The outputs of these methods are evaluated through various measures such as fuzziness, specificity, validity, and sigma-count. We illustrate that certain linguistic methods may result...