| Since the beginning, the internet has provided us with various different methods of gathering the user's reviews on almost everything. Among those various options, one of the possible ways is using a web based application. Earlier, methods of getting a review included mail, telephone and personal talk. Now, in addition to these traditional methods we can get reviews from people with just a few clicks and in less than no time.;My aim was to develop a review based search engine that will allow users to get reviews or opinions about a product based on the available information.;In this application, I am getting a raw dataset from Twitter using the Twitter's rest API having OAuth for authorization. The responses are in JSON and unstructured, hence using Mongo DB (NO SQL database) for storing them. To analyze the tweets, I have used APACHE Open NLP, sentiwordnet packages. The images of the products are retrieved using the Google API for images.;The purpose of the paper is to provide the ground level concept of creating and developing a user-friendly review based search engine, which can be further extended to a larger scale, adding more features to support detailed level review of a particular product. |
