Earticle

초록

영어

With the rapid development of digital libraries, name disambiguation becomes more and more important technique to distinguish authors with same names from physical persons. Many algorithms have been developed to accomplish the task. However, they are usually based on some restricted preconditions and rarely concern how to be incorporated into a practical application. In this paper, name disambiguation is regarded as the technique of learning module integrated with a knowledge base. A network is defined for the modeling of publication information, which facilitates the representation of differenttypes of relations among the attributes. The knowledge base component serves as the user interface for domain knowledge input. Furthermore, this paper exploits a random walk with restart algorithm and affinity propagation clustering algorithm to finally output name disambiguation results.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Preliminary
  3.1 Name Disambiguation
  3.2 Bi-Relational Network
  3.3 Random Walk with Restart (RWR)
 4. Our Method
  4.1 System Architecture
  4.2 Problem and Knowledge Representation
  4.3 Closeness Calculation andClustering
 5. Conclusions and Future Work
 Acknowledgments
 References

키워드

저자

• Yuechang Liu [ School of Computer Science, South China Normal University, School of Computer Science, Jiaying University ]
• Yong Tang [ School of Computer Science, South China Normal University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605