Restaurant Review Analysis
The objective of this project is to perform aspect-based sentiment analysis on restaurant reviews using natural language processing techniques to identify the aspects or features of the restaurant that customers are most satisfied or dissatisfied with, and to provide insights that can help restaurant owners and managers make data-driven decisions to improve the quality of their services and enhance the overall customer experience.
Identifying the aspects or features of the restaurant that are mentioned in the reviews using techniques such as Part-of-Speech (POS) tagging, dependency parsing, or Named Entity Recognition (NER).
Analyzing the sentiment expressed towards each aspect using techniques such as lexicon-based sentiment analysis, machine learning-based sentiment analysis, or hybrid approaches.
Visualizing the results of the sentiment analysis to provide insights into the overall sentiment of the restaurant and its various aspects using techniques such as bar graphs, word clouds, or heat maps.
Technologies that we use
- Flask
- Machine Learning
- Natural Language Processing
AI
Python
Machine Learning
