Abstract not found

Abstract-Relaxation labeling processes have been widely used in many different domains including image processing, pattern recognition, and artificial intelligence. They are iterative procedures that aim at reducing local ambiguities and achieving global consistency through a parallel exploitation of contextual information, which is quantitatively expressed in terms of a set of “compatibility coefficients. ” The problem of determining compatibility coefficients has received a considerable attention in the past and many heuristic, statistical-based methods have been suggested. In this paper, we propose a rather different viewpoint to solve this problem: we derive them attempting to optimize the performance of the relaxation algorithm over a sample of training data; no statistical interpretation is given: compatibility coefficients are simply interpreted as real numbers, for which performance is optimal. Experimental results over a novel application of relaxation are given, which prove the effectiveness of the proposed approach. Index Terms- Compatibility coefficients, constraint satisfaction, gradient projection, learning, neural networks, nonlinear

Relaxation labelling is an optimization technique used in many fields to solve constraint satisfaction problems. The algorithm finds a combination of values for a set of variables such that satisfies -- to the maximum possible degree -- a set of given constraints. This pat)er scribes some experiments performed applying it to POS tagging, and the results obtained. it also ponders the possibility of applying it, to Word Sense Disambiguation.

This paper explores the automatic construction of a multilingual Lexical Knowledge Base from preexisting lexical resources. This paper presents a new approach for linking already existing hierarchies. The Relaxation labeling algorithm is used to select --among all the candidate connections proposed by a bilingual dictionary-- the right conection for each node in the taxonomy. 1 Introduction There is no doubt about the increasing need of owning accurate and broad coverage general lexical/semantic resources for developing NL applications. Thus, one of the main issues in last years as regards NLP activities has been focused on the fast development of generic language resources. These resources include lexicons, lexical databases (ldbs), lexical knowledge bases (lkbs), ontologies, etc. Special interest presents, for knowledge-based NLP tasks, the availability of wide coverage ontologies. Most known ontologies (suchas gum, cyc, Ontos, Microkosmos, edr or WordNet, see [G'o98] for an extens...

Relaxation labelling is an optimization technique used in many fields to solve constraint satisfaction problems (CSP). The algorithm finds a combination of values for a set of variables such that satisfies-to the maximum possible degree- a set of given constraints. This paper describes some experiments performed applying it to POS tagging and the constraints used.