A comparison between neural networks and support vector machine approaches in Tagalog part-of-speech tagging - Reyes, Camille Dominique E.
Part-of-Speech (POS) Tagging is a fundamental process when it comes Natural Language Processing (NLP). In order to create applications that process data automatically, identifying each token's part of speech is usually the first step. However, there has been minimal effort. when it comes to NLP in the Philippines. And although there are existing POS taggers for Tagalog, they are still not as robust compared to POS taggers available for other languages. This paper explores the use of two widely used approaches in data classification namely, Neural Networks and Support Vector Machines in Part-of-Speech Tagging of Tagalog words. The use of bi-grams as word features was also implemented in both of our systems. Our Neural Network and SVM taggers both managed to out-perform existing Tagalog Part-of-Speech Taggers reaching accuracies of 86% and 89% respectively.