AUTOMATIC SPECIALIZED VS. NON-SPECIALIZED TEXTS DIFFERENTIATION: A FIRST APPROACH
Abstract
In this paper we would like to show that certain grammatical features, besides lexicon, have a strong potential to differentiate specialized texts from non-specialized texts. We have developed a tool including these features and it has been trained using machine learning techniques based on association rules using two sub-corpora (specialized vs. non-specialized), each one divided into training and test corpora. We have evaluated this tool and the results show that the strategy we have used is suitable to differentiate specialized texts from plain texts. These results could be considered as an innovative perspective to research on domains related with terminology, specialized discourse and computational linguistics, with applications to automatic compilation of Languages for Specific Purposes (LSP) corpora and optimization of search engines among others.
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