PRODUCT IDENTIFICATION USING FEATURE EXTRACTION AND OPINION MINING

The goal of this project is to create a system for product identification and feature extraction from textual data using natural language processing (NLP).Preprocessing data is required, along with the use of named entity identification and sentiment analysis algorithms for product categorization and feature extraction.The system uses text summarization techniques to produce succinct summaries.In the end, the project aims to identify products, extract features, analyze feelings, and generate summaries that are informative in order to automate product analysis.The results can be used as a useful tool for consumers and businesses alike for market research, product enhancement, and recommendation systems.