An OWA-Based Ranking Approach for University Books Recommendation

Sohail, S.S. and Siddiqui ., J and Ali, R (2018) An OWA-Based Ranking Approach for University Books Recommendation. International Journal of Intelligent Systems, 33 (2). pp. 396-416. ISSN 8848173

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Generally the book recommendation approaches are personalized in nature, that is, they utilize the users’ purchasing behavior to recommend them the book similar to their preferences. The main problem with the personalized recommendation is its knowledge requirement about users’ past preferences. As a result, these techniques fail in producing appropriate recommendation for a new user whose preferences are not known. The personalized recommendation also needs extra space to store the users’ preferences. In this paper, a framework to recommend books to university students for their studies is presented. In order to answer which books are to be included in the syllabus, a specialized way of recommendation, where recommendations from experts of the subjects at different universities are considered, is presented. We have suggested a ranked recommendation approach for books, which employ Ordered Weighted Aggregation (OWA), a fuzzy-based aggregation, to aggregate the several ranking of the top universities. On the one hand, it does not need user prior preferences, and on the other hand, it eases the complexities of personalized recommendation to huge number of users and replaces it with a single ranked recommendation. The experimental results are compared with the existing positional aggregation algorithm that demonstrates significant improvement in the results with respect to various performance metrics. © 2017 Wiley Periodicals, Inc.

Item Type: Article
Subjects: Q Science > Q Science (General)
Divisions: Faculties > Faculty of Science > Department of Computer Science
Depositing User: AMU Library
Date Deposited: 18 Jan 2018 10:44
Last Modified: 18 Jan 2018 10:44

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