Rating prediction and email query processing

This paper is mainly used for review rating prediction and email query processing. The rating for a specific product is generated from the review given by the customers. Here we use part of speech taggers and comparative analysis of the retrieved study to extract the emotions of the reviewers. We are using sentimental analysis to brings out trustworthiness. Instead of giving a rating option to customers, the rating is generated by the system. And the benefits of email query processing, it reduces the time consumption in web browsing. The query from the email holder (subject tag) is received from an inbox that the user has processed. A website can comfortably be scraped for the specific information of interest, summarizing them based on the question. It can later be presented to the required mail holders as an excel attachment for a call on what to do next. One of the models is the email query processing system. The e-commerce website data execution is extracted and converted into excel (CSV extension). The obtained excel sheet is now stored on the desktop. The data is scrapped by the UI path tool. The body of the mail is read using "let IMAP mail activity". By operating system, net, mail, mail message, body for the loop is obtained. The 993 pot is used in IMAP and serves imap.gmail.com with secure SSL for data authentication and encryption. In the rating prediction system, the passage is figured out based on the sentimental analysis. The words are assigned to their corresponding semantic role. This is called part of speech. Then the taggers for the related terms are identified.