RNA structure prediction is one of the major topics in bioinformatics. Among the various RNA structures, pseudoknots are the most complex and unique structure. Various methods have been used for modeling RNA pseudoknotted secondary structure. In this paper a new model for prediction of RNA pseudoknot structure has been proposed. In this model, features of two existing techniques, i. e. neural n...

In this paper we compare different approaches to extract definitions of four types using a combination of a rule-based grammar and machine learning. We collected a Dutch text corpus containing 549 definitions and applied a grammar on it. Machine learning was then applied to improve the results obtained with the grammar. Two machine learning experiments were carried out. In the first experiment,...

The purpose of this work is to investigate the process of grammatical acquisition from data. In order to do that, a computational learning system is used, composed of a Universal Grammar with associated parameters, and a learning algorithm, following the Principles and Parameters Theory. The Universal Grammar is implemented as a Unification-Based Generalised Categorial Grammar, embedded in a de...

Writing deep linguistic grammars has been considered a highly specialized skill, requiring the use of tools with steep learning curves and complex installation procedures. As the use of statistical methods has increased, new generations of computational linguists are getting less and less prepared for grammar writing tasks. In an aim to provide a better learning experience for grammar writers, ...