Hybrid Recommender System via Personalized Users’ Context-Reference-Cited by-同舟云学术

Hybrid Recommender System via Personalized Users’ Context

Published:2019-03-01 Issue:1 Volume:19 Page:101-115
ISSN:1314-4081
Container-title:Cybernetics and Information Technologies
language:en
Short-container-title:

Author:

Nosshi Anthony¹,Asem Aziza¹,Senousy Mohamed Badr²

Affiliation:

1. Information System Dept., Computers and Information Faculty , Mansoura University , Mansoura , Egypt

2. Computer and Information System Department , Sadat Academy for Management Sciences , Cairo , Egypt

Abstract

Abstract In movie domain, finding the appropriate movie to watch is a challenging task. This paper proposes a recommender system that suggests movies in cinema that fit the user’s available time, location, mood and emotions. Conducted experiments for evaluation showed that the proposed method outperforms the other baselines.

Publisher

Walter de Gruyter GmbH

Subject

General Computer Science

Link

https://www.sciendo.com/pdf/10.2478/cait-2019-0006

Reference27 articles.

1. 1. Champiri, Z. D., S. R. Shahamiri, S. S. B. Salim. A Systematic Review of Scholar Context-Aware Recommender Systems. – Expert Syst. Appl., Vol. 42, 2015, No 3, pp. 1743-1758.

2. 2. Shu, J., X. Shen, H. Liu, B. Yi, Z. Zhang. A Content-Based Recommendation Algorithm for Learning Resources. – Multimed. Syst., Vol. 24, 2018, No 2, pp. 163-173.

3. 3. Fu, M., H. Qu, D. Moges, L. Lu. Attention Based Collaborative Filtering. – Neurocomputing, Vol. 311, 2018, pp. 88-98.

4. 4. Wang, F., S. Lin, X. Luo, H. Wu, R. Wang, F. Zhou. A Data-Driven Approach for Sketch-Based 3D Shape Retrieval via Similar Drawing-Style Recommendation. – Comput. Graph. Forum, Vol. 36, October 2017, No 7, pp. 157-166.

5. 5. Chu, P. M., S. J. Lee. A Novel Recommender System for e-Commerce. – In: Proc. of 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI’17), 2017, pp. 1-5.

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Searching, Navigating, and Recommending Movies through Emotions: A Scoping Review;Human Behavior and Emerging Technologies;2022-12-02

2. Smart recommendation for tourist hotels based on multidimensional information: a deep neural network model;Enterprise Information Systems;2021-08-02

3. Communication-Based Book Recommendation in Computational Social Systems;Complexity;2021-01-29

4. Expert system for digital single lens reflex (DSLR) camera recommendation using forward chaining and certainty factor;INTERNATIONAL CONFERENCE ON MATHEMATICS, COMPUTATIONAL SCIENCES AND STATISTICS 2020;2021