This contribution proposes a Genetic Algorithm for jointly performing a feature selection and granularity learning for Fuzzy RuleBased Classification Systems in the scenario of data-sets with a high imbalance degree. We refer to imbalanced data-sets when the class distribution is not uniform, a situation that it is present in many real application areas. The aim of this work is to get more comp...

In this paper, we describe the process of rulebased conversion of Russian dependency treebank into the Stanford dependency (SD) schema. The motivation behind this project is the expansion of the number of languages that have treebank resources available in one consistent annotation schema. Conversion includes creation of Russian-specific SD guidelines, defining conversion rules from the origina...

Despite the recent advances in parsing, significant efforts are needed to improve the current parsers performance, such as the enhancement of the argument/adjunct recognition. There is evidence that verb subcategorization frames can contribute to parser accuracy, but a number of issues remain open. The main aim of this paper is to show how subcategorization frames acquired from a syntactically ...

Automated essay marking systems developed from late 1960’s attempted to prove that a computer can mark essays as good as any other human beings. This paper discusses an approach for developing an automated marking tool for English as a second language (ESL) and introduces heuristics and rulebased approach to detect grammatical errors in tenses in ESL essays. The results show that heuristics and...