Name
Abstract | ||
|---|---|---|
AbstractDeep learning has become popular in all aspect related to human judgments. Most machine learning techniques work well which includes text classification, text sequence learning, sentiment analysis, question-answer engine, etc. This paper has been focused on two objectives, firstly is to study the applicability of deep neural networks strategies for extracting sentiment present in social media data and customer reviews with effective training solutions. The second objective is to design deep networks that can be trained with these weakly supervised strategies in order to predict meaningful inferences. This paper presents the concept and steps of using deep learning for extraction sentiments from customer reviews. The extraction pulls out the features from the customer reviews using deep learning popular methods including Convolution neural networks CNN and Long Short-Term Memory LSTM architectures. The comparison of the results with tradition text classification method such as Naive BayesNB and Support Vector MachineSVM using two data sets IMDB reviews and Amazon customer reviews have been presented. This work mainly focused on investigating the merit of using deep models for sentiment analysis in customer reviews. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.4018/IJEIS.2018040105 | Periodicals |
Keywords | Field | DocType |
Deep Learning, Machine Learning, Sentiment Analysis, Social Media, Text Mining | Knowledge management,Customer reviews,Artificial intelligence,Engineering,Deep learning | Journal |
Volume | Issue | ISSN |
14 | 2 | 1548-1115 |
Citations | PageRank | References |
3 | 0.39 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vinay Kumar Jain | 1 | 10 | 1.56 |
| Shishir Kumar | 2 | 78 | 17.06 |
| Prabhat Mahanti | 3 | 40 | 5.03 |