A Hybrid System for Subjectivity Analysis

Abstract

We suggested different structured hybrid systems for the sentence-level subjectivity analysis based on three supervised machine learning algorithms, namely, Hidden Markov Model, Fuzzy Control System, and Adaptive Neuro-Fuzzy Inference System. The suggested feature extraction algorithm in our experiment computes a feature vector using statistical textual terms frequencies in a training dataset not having the use of any lexical knowledge except tokenization. Taking into consideration this fact, the above-mentioned methods may be employed in other languages as these methods do not utilize the morphological, syntactical, and lexical analysis in the classification problems.