… some literature that used Deep Learning to solved problems related to text mining and NLP.
This review was conducted on over 50 studies undertook Deep Learning development. The …

… text mining approach to analyze MOOC reviews, with the use of machine learning,
ensemble learning, and deep learning … To process text, we have utilized five deep learning …

… on deep learning over the past 10 years. We collected research literature on deep learning
… The results of this study will provide insights into research direction on deep learning in the …

… , statistical modeling, and machine learning (ML) … learning and deep learning models [6],
[7], [8]. This paper introduces a new LSTM-Glove based deep learning model for enhancing text …

… at new applications, deep learning enables to … deep learning has made achievements in
text mining. The major difference between deep learning and conventional methods is that deep …

… In particular, we propose a solution based on a deep learning model that automatically
extracts the main topics that are covered in educational documents. This model is next applied to …

… in an unstructured or semi-structured text format. In the case of … Drawing on text mining and
deep learning technologies the … brief review of the text mining and deep learning literature to …

… though deep semi-supervised learning methods have begun to be used for some text mining
… use of self-supervised learning and unsupervised learning in text mining. A characteristic …

… In the case study of this paper, we explore local learning for text mining methods that use
word embedding. This is the process of converting words to vectors in order to compare their …

… mining. We think that deep learning will have many more successes in the near future in
biomedical text mining domain because it requires very little engineering by hand, so it can …