원문정보
보안공학연구지원센터(IJGDC)
International Journal of Grid and Distributed Computing
Vol.9 No.7
2016.07
pp.23-32
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In order to solve this problem of cloud model, this paper presents another new collaborative filtering recommendation algorithm by combining the item classification and cloud model. Firstly the algorithm utilizes the item classification information and cloud model to compute items inner-similarity, and then gets the scores from neighbor items which have the highest similarity and uses their scores to forecast the unrated inner-class items. Secondly, the neighbors of user are obtained by computing the inner-class user similarities in the cloud model, providing the final forecast grade and carrying out the recommendation.
목차
Abstract
1. Introduction
2. Collaborative Filtering Improvement Algorithm based on Cloud Model
2.1. Similarity Measurement Methods based on Cloud Model
2.2. Score Forecasting Algorithm of the Cloud Model
2.3. Collaborative Filtering Improved Algorithm based on Cloud Model
3. Experiment Design and Discussion
3.1 Experimental Dataset
3.2 Evaluation Criteria
3.3 Experiment and Result Analysis
5. Conclusion
Acknowledgement
References
1. Introduction
2. Collaborative Filtering Improvement Algorithm based on Cloud Model
2.1. Similarity Measurement Methods based on Cloud Model
2.2. Score Forecasting Algorithm of the Cloud Model
2.3. Collaborative Filtering Improved Algorithm based on Cloud Model
3. Experiment Design and Discussion
3.1 Experimental Dataset
3.2 Evaluation Criteria
3.3 Experiment and Result Analysis
5. Conclusion
Acknowledgement
References
저자정보
참고문헌
자료제공 : 네이버학술정보