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The Scientific World Journal
Volume 2013, Article ID 869658, 9 pages
http://dx.doi.org/10.1155/2013/869658
Research Article

A New Collaborative Recommendation Approach Based on Users Clustering Using Artificial Bee Colony Algorithm

1Center for Studies of Modern Business, Zhejiang Gongshang University, Hangzhou 310018, China
2College of Computer Science & Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China
3College of Business Administration, Zhejiang Gongshang University, Hangzhou 310018, China

Received 5 September 2013; Accepted 17 October 2013

Academic Editors: T. Chen and J. Yang

Copyright © 2013 Chunhua Ju and Chonghuan Xu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [15 citations]

The following is the list of published articles that have cited the current article.

  • Tingwei Gao, Xiu Li, Yueting Chai, and Youhua Tang, “Deep learning with consumer preferences for recommender system,” 2016 IEEE International Conference on Information and Automation (ICIA), pp. 1556–1561, . View at Publisher · View at Google Scholar
  • Alisa Sotsenko, Marc Jansen, Marcelo Milrad, and Juwel Rana, “Using a Rich Context Model for Real-Time Big Data Analytics in Twitter,” 2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW), pp. 228–233, . View at Publisher · View at Google Scholar
  • Chunhua Ju, and Chonghuan Xu, “Personal Recommendation Via Heterogeneous Diffusion on Bipartite Network,” International Journal on Artificial Intelligence Tools, vol. 23, no. 3, 2014. View at Publisher · View at Google Scholar
  • Haoran Xie, Xiaodong Li, Jiantao Wang, Qing Li, and Yi Cai, “The Collaborative Search by Tag-Based User Profile in Social Media,” The Scientific World Journal, vol. 2014, pp. 1–7, 2014. View at Publisher · View at Google Scholar
  • Bai Li, Li-Gang Gong, and Ya Li, “A Novel Artificial Bee Colony Algorithm Based on Internal-Feedback Strategy for Image Template Matching,” The Scientific World Journal, vol. 2014, pp. 1–14, 2014. View at Publisher · View at Google Scholar
  • Shu-Lin Wang, Young Long Chen, Alex Mu-Hsing Kuo, Hung-Ming Chen, and Yi Shiang Shiu, “Design and evaluation of a cloud-based Mobile Health Information Recommendation system on wireless sensor networks,” Computers & Electrical Engineering, 2015. View at Publisher · View at Google Scholar
  • Mu-Hsing Kuo, Hsiu-Mei Huang, Shu-Lin Wang, and Yi-Shiang Shiu, “A Recommendation-based Mobile Web Application for Health Information Service,” Studies in Health Technology and Informatics, vol. 208, pp. 337–341, 2015. View at Publisher · View at Google Scholar
  • Punam Bedi, Shikha Agarwa, Archana Singhal, Ena Jain, Gunjan Gupta, Punam Bedi, Shikha Agarwa, Archana Singhal, Ena Jain, and Gunjan Gupta, “A Novel Semantic Clustering Approach for Reasonable Diversity in News Recommendations,” Computational Intelligence In Data Mining, Vol 1, vol. 31, pp. 437–445, 2015. View at Publisher · View at Google Scholar
  • Vedant Choudhary, Dhruv Mullick, and Sushama Nagpal, “Gravitational Search Algorithm in Recommendation Systems,” Advances in Swarm Intelligence, vol. 10386, pp. 597–607, 2017. View at Publisher · View at Google Scholar
  • Chunhua Ju, and Wanqiong Tao, “A novel relationship strength model for online social networks,” Multimedia Tools and Applications, 2017. View at Publisher · View at Google Scholar
  • Ajit Kumar, Dharmender Kumar, and Jarial, “A review on artificial bee colony algorithms and their applications to data clustering,” Cybernetics and Information Technologies, vol. 17, no. 3, pp. 3–28, 2017. View at Publisher · View at Google Scholar
  • Chunhua Ju, Jie Wang, and Chonghuan Xu, “A novel application recommendation method combining social relationship and trust relationship for future internet of things,” Multimedia Tools and Applications, 2018. View at Publisher · View at Google Scholar
  • Muhammad Aqib Javed, Muhammad Shahzad Younis, Siddique Latif, Junaid Qadir, and Adeel Baig, “Community detection in networks: A multidisciplinary review,” Journal of Network and Computer Applications, 2018. View at Publisher · View at Google Scholar
  • Anitha Anandhan, Liyana Shuib, Ghulam Mujtaba, and Maizatul Akmar Ismail, “Social Media Recommender Systems: Review and Open Research Issues,” IEEE Access, vol. 6, pp. 15608–15628, 2018. View at Publisher · View at Google Scholar
  • Monika Singh, “Scalability and sparsity issues in recommender datasets: a survey,” Knowledge and Information Systems, 2018. View at Publisher · View at Google Scholar