Earticle

초록

영어

Searching for similar documents from huge amounts of documents is an important and time consuming problem. Although the numerous precise models have been developed for the task, the traditional search algorithms are unable to meet the needs of users for quick search. Herein, a new document similarity calculation and search method with high efficiency is proposed. The calculation of the similarity is based on the total probability model and the efficient search is achieved via level n nodes and paths of citation graph. A special approach from the branch and bound limits the search scope and provide decision algorithm. With the increase in the number of documents, the efficiency of the proposed algorithm is dramatically promoted.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Document Similarity Calculation
  3.1. Basic Graph Model
  3.2 Adjacent Nodes Similarity Calculation
  3.3 Non Adjacent Nodes Similarity Calculation
 4. Document Similarity Search Algorithm
  4.1 Problem Description
  4.2 Search Algorithm
  4.3 Analysis of Search Algorithm Efficiency
 5. Experiments
  5.1 Experimental Data and Environment
  5.2 Evaluation Measure
  5.3 Experimental Methods and Results
 6. Conclusion
 References

키워드

저자

• Zhu Ge [ Department of Information Science and Technology, Heilongjiang University, 74 Xue Fu Road, Harbin, 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