JOURNAL ARTICLE

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

Abstract

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 try to establish an 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

Keywords:
Collaborative filtering Rough set Cluster analysis Computer science Recommender system Data mining Set (abstract data type) Algorithm Statistical classification Artificial intelligence Machine learning

Metrics

4
Cited By
0.00
FWCI (Field Weighted Citation Impact)
1
Refs
0.13
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Rough Sets and Fuzzy Logic
Physical Sciences →  Computer Science →  Computational Theory and Mathematics
E-commerce and Technology Innovations
Social Sciences →  Business, Management and Accounting →  Business and International Management
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