Earticle

초록

영어

The personalized recommendation systems could better improve the personalized service for network user and alleviate the problem of information overload in the Internet. As we all know, the key point of being a successful recommendation system is the performance of recommendation algorithm. When scholars put forward some new recommendation algorithms, they claim that the new algorithms have been improved in some respects, better than previous algorithm. So we need some evaluation metrics to evaluate the algorithm performance. Due to the scholar didn’t fully understand the evaluation mechanism of recommendation algorithms. They mainly emphasized some specific evaluation metrics like Accuracy, Diversity. What’s more, the academia did not establish a complete and unified assessment of recommendation algorithms evaluation system which is credibility to do the work of recommendation evaluation. So how to do this work objective and reasonable is still a challengeable task. In this article, we discussed the present evaluation metrics with its respective advantages and disadvantages. Then, we put forward to use the Matthews Correlation Coefficient to evaluate the recommendation algorithm’s performance. All this based on an open source projects called mahout which provides a rich set of components to construct the classic recommendation algorithm. The results of the experiments show that the applicability of Matthews correlation coefficient in the relative evaluation work of recommendation algorithm.

목차

Abstract
 1. Introduction
 2. Related Work
 3. MCCP Evaluation Metric
  3.1. The Definition of MCCP
  3.2. The Algorithm Analysis
 4. Experimental Evaluation
  4.1. Experimental Environment
  4.2. Experiment Results
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Yingbo Liu [ Key Laboratory of Embedded System and Service Computing of Ministry of Education, Tongji University, Shanghai 201804, China, Department of Computer Science and Technology, Tongji University, Shanghai 201804, China ]
• Jiujun Cheng [ Key Laboratory of Embedded System and Service Computing of Ministry of Education, Tongji University, Shanghai 201804, China, Department of Computer Science and Technology, Tongji University, Shanghai 201804, China ] Corresponding author.
• Chendan Yan [ Key Laboratory of Embedded System and Service Computing of Ministry of Education, Tongji University, Shanghai 201804, China, Department of Computer Science and Technology, Tongji University, Shanghai 201804, China ]
• Xiao Wu [ Key Laboratory of Embedded System and Service Computing of Ministry of Education, Tongji University, Shanghai 201804, China, Department of Computer Science and Technology, Tongji University, Shanghai 201804, China ]
• Fuzhen Chen [ Key Laboratory of Embedded System and Service Computing of Ministry of Education, Tongji University, Shanghai 201804, China, Department of Computer Science and Technology, Tongji University, Shanghai 201804, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605