Abstract:  Automated Essay Scoring (AES) is a challenging task which assigns grades to essays written in an educational institute. It reduces human errors, inequality problem, time consuming and so on. There are diverse approaches for this task like natural language processing, machine learning, deep learning etc. The overall performance of such systems is tightly bound to high-quality features. The essential purpose of this paper is to evaluate these strategies of AES in both in-domain and cross domain settings.

Keywords:  Convolution Neural Network (CNN), Long Short-Term Memory (LSTM), Deep Learning, Natural language Processing

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