Scopus Indexed Publications
Paper Details
- Title
- Sentiment Analysis of Restaurant Reviews using Combined CNN-LSTM
- Author
- Naimul Hossain, Md. Rafiuzzaman Bhuiyan, Syed Akhter Hossain, Zerin Nasrin Tumpa,
- aktarhossain@daffodilvarsity.edu.bd
- Abstract
- The combination of machine learning approach and natural language processing is applied to analyze the sentiment of text for particular sentences. In this particular area lots of work done in recent times. Restaurant business was always a popular business in Bangladesh. These business is now Leaning towards online delivery services and the overall quality of restaurants are now judged by reviews of customers. One try to understand the quality of a restaurant by the reviews from other customers. These opinions of customers organizing in structured way and to understand perception of customers reviews and reactions is the main motto of our work. Collecting data was the first thing we have done for deploying this piece of work. Then making a dataset which we harvested from websites and tried to deploy with deep learning technique. In this piece of research, a combined CNN-LSTM architecture used in our dataset and got an accuracy of 94.22%. Also used some other performance metrics to evaluate our model.
- Keywords
- Sentiment analysis , Combined CNN-LSTM , Text classification , Deep learning , Word embedding
- Journal or Conference Name
- 11th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2020
- Publication Year
- 2020
- Indexing
- scopus