원문정보
보안공학연구지원센터(IJUNESST)
International Journal of u- and e- Service, Science and Technology
Vol.9 No.3
2016.03
pp.169-178
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
An improved CF algorithm based on the classification of items is introduced to overcome the problems caused by the data sparseness and inaccuracy of the user neighbors. The new algorithm first rates the unrated items by applying the item classification, and then calculates the user similarity within classes for nearest-neighbors, after which it could recommend the items based on the final prediction.
목차
Abstract
1. Introduction
2. The Improved Collaborative Filtering Algorithm Based on Item Classification
2.1. Traditional Collaborative Filtering Algorithms
2.2. Method for Predicting Scores of Unrated Items Based on Item Classification
2.3. Improved Collaborative Filtering Algorithm Based on Item Classification
3. Experiment Design and Discussion
3.1. Experimental Dataset
3.2. Evaluation Criteria
3.3. Experiment and Result Analysis
4. Conclusion
References
1. Introduction
2. The Improved Collaborative Filtering Algorithm Based on Item Classification
2.1. Traditional Collaborative Filtering Algorithms
2.2. Method for Predicting Scores of Unrated Items Based on Item Classification
2.3. Improved Collaborative Filtering Algorithm Based on Item Classification
3. Experiment Design and Discussion
3.1. Experimental Dataset
3.2. Evaluation Criteria
3.3. Experiment and Result Analysis
4. Conclusion
References
저자정보
참고문헌
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