Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: Special Section: Intelligent, Smart and Scalable Cyber-Physical Systems
Guest editors: V. Vijayakumar, V. Subramaniyaswamy, Jemal Abawajy and Longzhi Yang
Article type: Research Article
Authors: Poongodi, M.a; * | Vijayakumar, V.a | Rawal, Bharatb | Bhardwaj, Vaibhava | Agarwal, Tanaya | Jain, Ankita | Ramanathan, L.c | Sriram, V.P.d
Affiliations: [a] Vellore Institute of Technology, Chennai, India | [b] Pen State University, USA | [c] Vellore Institute of Technology, Vellore, India | [d] Acharya Banglore Business School, Bangalore
Correspondence: [*] Corresponding author. M. Poongodi, Vellore Institute of Technology, Chennai, India. E-mail: [email protected].
Abstract: Nowadays, the purchase of every product involves a lot of critical thinking. Every buyer goes through a lot of user reviews and rating before finalizing his purchase. They do this to ensure that the product they purchase is of good quality at minimum price possible. It is evident now that online reviews are not that reliable because of fake reviews and review bots. Now you can even pay certain social media groups to give your product a fake good rating. Hence going just with the reviews of some stranger whom you do not know is not intelligent. So we propose a recommendation model based on the Trust Relations (TR) and User Credibility (UC) because it is human nature that a person feels more comfortable when he gets a review from a person he knows on a first name basis. Also, the credibility of the reviewer is an important factor while providing importance to the reviews because every person is different from other and can have different expertise. Our model takes into account the effect of credibility which is not used by any other recommendations models which increases the precision of the results of our model. We also propose the algorithm to calculate the credibility of any node in the network. The results are validated using a dataset and applying our proposed model and traditional average rating model which shows that our model performs better and gives precise results.
Keywords: Recommendation, trust relations, social network, user credibility
DOI: 10.3233/JIFS-169966
Journal: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 5, pp. 4057-4064, 2019
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]