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A Mathematical Recommendation Model to Rank Reviewers Based on Weighted Score for Online Review System
R. Ganguli, P. Banerjee, S. Halder,
Published in Springer Science and Business Media Deutschland GmbH
Volume: 164
Pages: 317 - 325
Recommendation systems play a very important role in business from several aspects. New systems, concepts are being evolved to enrich the business from different perspectives. Online reviews provide valuable information about products and services to consumers. Generally, online reviews are done on products to understand the usefulness or popularity of a product. However, it is being found that often fake reviews are given to increase the popularity of own product or to defame competitors’ products. This imposes research challenge to validate the reviews or Trustworthiness of reviewers. A recommendation model in online review system aims to filter the authenticated reviewers and then rank the top reviewers or emphasize on more impactful reviews. In this paper, a mathematical model is presented to rank the reviewers by assigning weighted scores based on certain parameters. A pre-processing technique is used before applying mathematical model to filter out the quality reviews. The pre-processing technique and data analysis are experimented on a real-life dataset to show the effectiveness of the proposed model. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetLecture Notes in Networks and Systems
PublisherData powered by TypesetSpringer Science and Business Media Deutschland GmbH