Open AccessAn Efficient Research Of Autoranking Of Amazon Research Using Regression Models
Author(s) -
Ankit Rawat,
Nitesh Gupta
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f1006.0886s19
Subject(s) - purchasing , computer science , product (mathematics) , audit , process (computing) , amazon rainforest , data science , work (physics) , marketing , business , engineering , mechanical engineering , ecology , geometry , mathematics , accounting , biology , operating system
Before providing services to customers it is very important to know about the requirements as well as the services or products we are providing them contains opinions of other customers in which manner like-it is a positive review from the customer or the negative review. Since, an opinion plays a very important role in purchasing anything. There are some sites running online for the purpose of providing goods to the customers also they focused onto taking the decision over the posting reviews whether it is a positive response or negative. The motive of the work is to analyse the social data or products reviews simultaneously, and then create a model that will automatically create a model for product review. This paper bringing the continuous audits from a web based business website amazon and apply different content mining methods to pre-process the information and afterward apply an AI approach through which results will assess the viability of surveys through an outstanding measure for decency of fit. In this paper a development model with a computational cost model is utilized. The improved cost model with the word handling and positioning is utilized in given research.