An Efficient Recommender System Based on Collaborative Filtering Recommendation and Cluster Ensemble

Hafed Zarzour, Faiz Maazouzi, Mohammad Al-Zinati, Yaser Jararweh, Thar Baker

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBNpeer-review

Abstract

In the last few years, cluster ensembles have emerged as powerful techniques that integrate multiple clustering methods into recommender systems. Such integration leads to improving the performance, quality and the accuracy of the generated recommendations. This paper proposes a novel recommender system based on a cluster ensemble technique for big data. The proposed system incorporates the collaborative filtering recommendation technique and the cluster ensemble to improve the system performance. Besides, it integrates the Expectation-Maximization method and the HyperGraph Partitioning Algorithm to generate new recommendations and enhance the overall accuracy. We use two real-world datasets to evaluate our system: TED Talks and MovieLens. The experimental results show that the proposed system outperforms the traditional methods that utilize single clustering techniques in terms of recommendation quality and predictive accuracy. Most importantly, the results indicate that the proposed system provides the highest precision, recall, accuracy, F1, and the lowest Root Mean Square Error regardless of the used similarity strategy.

Original languageEnglish
Title of host publication2021 8th International Conference on Social Network Analysis, Management and Security, SNAMS 2021
EditorsChristian Guetl, Paolo Ceravolo, Yaser Jararweh, Elhadj Benkhelifa, Oluwasegun Adedugbe
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665494953
DOIs
Publication statusPublished - 6 Dec 2021
Event8th International Conference on Social Network Analysis, Management and Security, SNAMS 2021 - Virtual, Gandia, Spain
Duration: 6 Dec 20219 Dec 2021

Publication series

Name2021 8th International Conference on Social Network Analysis, Management and Security, SNAMS 2021

Conference

Conference8th International Conference on Social Network Analysis, Management and Security, SNAMS 2021
Country/TerritorySpain
CityVirtual, Gandia
Period6/12/219/12/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

  • cluster ensemble
  • collaborative filtering recommendation
  • EM
  • Expectation Maximization
  • recommender system
  • recommender system for big data

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