| Popis: |
Emotion recognition is a topic of vital importance in the world of Big Data. The accurate classification, analysis and interpretation of emotional content is highly desired in a wide spectrum of applications. In this work we examine the performance of Deep Learning models for an emotion recognition task. These models can also be applied to any classification task as well as text-related tasks in general. We examine the performance of deep learning methods in textual emotion recognition under different feature selection parameters such as one-hot-enconding, custom word2vec and more. An experimental study was designed and various deep learning methods were evaluated in publicly available datasets. The results are quite interesting and indicate the advantages of each method and each examined training approach. |
