A Rough Set-Based Clustering Collaborative Filtering Algorithm in E-commerce Recommendation System

Rough set is a new mathematical tool that deal with incomplete and uncertain knowledge, it can improve the classification accuracy because of its characteristics. Recommendation algorithm is the core of the recommendation system. In this paper, a rough set-based clustering collaborative filtering al...

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Bibliographic Details
Main Authors: Yongjian Fan, Jianying Mai, Xiaofei Ren
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Artificial intelligence
clustering algorithm
Clustering algorithms
Collaboration
collaborative filtering algorithm
Data mining
Filtering algorithms
Information management
Knowledge representation
Pattern recognition
recommendation algorithm
rough set
Rough sets
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Summary:Rough set is a new mathematical tool that deal with incomplete and uncertain knowledge, it can improve the classification accuracy because of its characteristics. Recommendation algorithm is the core of the recommendation system. In this paper, a rough set-based clustering collaborative filtering algorithm in e-commerce recommendation system is designed. This paper tries to establish a classifier model based on rough set for the pre-classification to items and give realization of clustering collaborative filtering algorithm and procedure of rough set algorithm, and carry on the analysis and discussion to this algorithm from multiple aspects. This algorithm is helpful to improve sparsity problem of collaborative filtering algorithm and to form the more effective and the more accurate recommendation results.
ISSN:2155-1456
2155-1472
DOI:10.1109/ICIII.2009.556