Identifying Portuguese Multiword Expressions using Different Classification Algorithms - A Comparative Analysis

Abstract

This paper presents a comparative analysis based on different classification algorithms and tools for the identification of Portuguese multiword expressions. Our focus is on two-word expressions formed by nouns, adjectives and verbs. The candidates are selected on the basis of the frequency of the bigrams; then on the basis of the grammatical class of each bigram's constituent words. This analysis compares the performance of three different multi-layer perceptron training functions in the task of extracting different patterns of multiword expressions, using and comparing nine different classification algorithms, including decision trees, multilayer perceptron and SVM. Moreover, this analysis compares two different tools, Text-NSP and Termostat for the identification of multiword expressions using different association measures.