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Association Rule Mining in Collaborative Filtering

Association Rule Mining in Collaborative Filtering

Carson K.-S. Leung, Fan Jiang, Edson M. Dela Cruz, Vijay Sekar Elango
Copyright: © 2017 |Pages: 21
ISBN13: 9781522504894|ISBN10: 1522504893|EISBN13: 9781522504900
DOI: 10.4018/978-1-5225-0489-4.ch009
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MLA

Leung, Carson K.-S., et al. "Association Rule Mining in Collaborative Filtering." Collaborative Filtering Using Data Mining and Analysis, edited by Vishal Bhatnagar, IGI Global, 2017, pp. 159-179. https://doi.org/10.4018/978-1-5225-0489-4.ch009

APA

Leung, C. K., Jiang, F., Dela Cruz, E. M., & Elango, V. S. (2017). Association Rule Mining in Collaborative Filtering. In V. Bhatnagar (Ed.), Collaborative Filtering Using Data Mining and Analysis (pp. 159-179). IGI Global. https://doi.org/10.4018/978-1-5225-0489-4.ch009

Chicago

Leung, Carson K.-S., et al. "Association Rule Mining in Collaborative Filtering." In Collaborative Filtering Using Data Mining and Analysis, edited by Vishal Bhatnagar, 159-179. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-0489-4.ch009

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Abstract

Collaborative filtering uses data mining and analysis to develop a system that helps users make appropriate decisions in real-life applications by removing redundant information and providing valuable to information users. Data mining aims to extract from data the implicit, previously unknown and potentially useful information such as association rules that reveals relationships between frequently co-occurring patterns in antecedent and consequent parts of association rules. This chapter presents an algorithm called CF-Miner for collaborative filtering with association rule miner. The CF-Miner algorithm first constructs bitwise data structures to capture important contents in the data. It then finds frequent patterns from the bitwise structures. Based on the mined frequent patterns, the algorithm forms association rules. Finally, the algorithm ranks the mined association rules to recommend appropriate merchandise products, goods or services to users. Evaluation results show the effectiveness of CF-Miner in using association rule mining in collaborative filtering.

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