Improving the performance of video Collaborative Filtering Recommender Systems using Optimization Algorithm

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TOHIDI N.; Dadkhah C.

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Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF NONLINEAR ANALYSIS AND APPLICATIONS Year:2020 | Volume:11 | Issue:1 Page(s): 483-495

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Information Journal Paper

Title

Improving the performance of video Collaborative Filtering Recommender Systems using Optimization Algorithm

Author(s)

TOHIDI N. | Dadkhah C. | Issue Writer Certificate

Keywords

recommender system

accelerated particle swarm optimization

forest optimization algorithm

collaborative ltering

clustering

Abstract

The growth amount of information on the Web makes it difficult for many web users to make decision and choose either information or goods. Thus, a recommender system is an approach that helps users to obtain their needs according to her/his preference within a massive amount of information rapidly without waste of time. The main advantage of using a recommender system in any online shopping or social media like Amazon, Net ix and Facebook is to increase the percentage of overall pro ts, customer satisfaction and retention. In this paper, we introduce an approach to increase the accuracy and to improve the performance of collaborative ltering recommender system. In this paper a hybrid approach is proposed to improve the performance of video collaborative ltering recommender system based on clustering and evolutionary algorithm. Proposed approach combines k-means clustering algorithm and two different evolutionary algorithms which are accelerated particle swarm optimization Algorithm (APSO) and forest optimization algorithm (FOA). The main aim of this paper is to increase the accuracy of recommendation of user-based collaborative ltering video recommender system. Evaluation and computational results on the MovieLens dataset show that the proposed method has a better performance than the other related methods.

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APA: Copy

TOHIDI, N., & Dadkhah, C.. (2020). Improving the performance of video Collaborative Filtering Recommender Systems using Optimization Algorithm. INTERNATIONAL JOURNAL OF NONLINEAR ANALYSIS AND APPLICATIONS, 11(1), 483-495. SID. https://sid.ir/paper/340823/en

Vancouver: Copy

TOHIDI N., Dadkhah C.. Improving the performance of video Collaborative Filtering Recommender Systems using Optimization Algorithm. INTERNATIONAL JOURNAL OF NONLINEAR ANALYSIS AND APPLICATIONS[Internet]. 2020;11(1):483-495. Available from: https://sid.ir/paper/340823/en

IEEE: Copy

N. TOHIDI, and C. Dadkhah, “Improving the performance of video Collaborative Filtering Recommender Systems using Optimization Algorithm,” INTERNATIONAL JOURNAL OF NONLINEAR ANALYSIS AND APPLICATIONS, vol. 11, no. 1, pp. 483–495, 2020, [Online]. Available: https://sid.ir/paper/340823/en

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