Earticle

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

키워드

저자

• Dan Zhang [ Institute of Technology, Mudanjiang normal university, Mudanjiang 157000, china ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605