Early Reviewers Prediction and Spammer Detection on E-Commerce Websites
Jayendra Kumar1, Palakursha Sirisha2
1Jayendra Kumar, Computer Science and Engineering, Anurag Group of Institutions, Hyderabad, India.
2Palakusha Sirisha, Computer Science and Engineering, Anurag Group of Institutions, Hyderabad, India. 

Manuscript received on November 20, 2019. | Revised Manuscript received on November 28, 2019. | Manuscript published on 30 November, 2019. | PP: 7859-7860 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8493118419/2019©BEIESP | DOI: 10.35940/ijrte.D8493.118419

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Reviews which are posted online play a vital part in present world as most of the customer’s purchase items through an e-commerce website. Reviews which are posted on websites at an early stage known as early reviews, even though their contribution is very small their opinions determine new product’s success and failure. Most of the spam reviews are written to improve their profit and promote their products and defame other products. In this system, the concentration is mainly on early reviews of the products and the products categories ranking on e-commerce websites i.e., Amazon. The analysis of reviews of product defines ratings of early reviewers’ and helpfulness scores of them are probably influencing product promotion additionally this model is enhanced with ranking and spammer detection. Keywords:
Keywords: Early Reviewers, E-Commerce, Ranking Model, Spammer..
Scope of the Article: E-Commerce.