Earticle

초록

영어

The manifold-ranking based method is widely used in semi-supervised learning, and its performance is closely related to the structure of the constructed graph. In this paper, we propose a novel graph structure named natural neighbor graph and an algorithm to construct it. We apply the new graph structure into the framework of manifold-ranking based image retrieval. The greatest superiority over k-NN based method is that the free parameter k need not to be explicitly specified any more. We have shown that the manifold ranking algorithm based on our proposed graph structure performs better than k-NN graph. Experiments demonstrate that the proposed algorithm outperforms the state-of-the-art algorithms.

목차

Abstract
 1. Introduction
 2. Related Works
 3. Natural Neighbor Graph 
  3.1 The Definition of Natural Neighbor Graph
  3.2 The Constructing Method of 2N Graph
  3.3 The Manifold-Ranking Method Based on 2N
 4. Experimental Result
 5. Conclusion and Future Work
 Acknowledgements 
 References

키워드

저자

• Qingsheng Zhu [ Chongqing Key Lab. of Software Theory and Technology College of Computer Science, Chongqing University, Chongqing 400044, China ]
• Zhi Chen [ Chongqing Key Lab. of Software Theory and Technology College of Computer Science, Chongqing University, Chongqing 400044, China ]
• Cheng Zhang [ Chongqing Key Lab. of Software Theory and Technology College of Computer Science, Chongqing University, Chongqing 400044, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605