• Anjali Dadh

On recent years, special attention has been giving also to the amount of produced user-generated content. The e-commerce sector is one of the most affected by the amount of data produced by customers, which increased dramatically during the phase known as Web 2.0. Customer’s opinions represent a valuable unique type of information which should not be mistreated or ignored by the research community. Thus, this work emphasizes the need of special mechanisms that aims to provide the community better ways to take full advantage from this data. From the customer perspective, considering others opinions before purchasing a product is a common behavior long before the existence of Internet. In the era of the digital world, the difference is that a customer has access to thousands of opinions, which greatly improves decision making. The proposed framework will combine several techniques to extract valuable information out of natural language text (user-generated content), in order to provide enrichment of the experience of users by taking advantage of the available content in a more intelligent and organized way.

Opinion Mining, NLP, Machine learning, Social media

"Algorithm for efficient Opinion Summarization and categorization (AEOSC): A web Based approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.624-627, June-2019, Available :http://www.jetir.org/papers/JETIR1907086.pdf

"Algorithm for efficient Opinion Summarization and categorization (AEOSC): A web Based approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp624-627, June-2019, Available at : http://www.jetir.org/papers/JETIR1907086.pdf