Earticle

초록

영어

For further solving the problem of normative emergency plan, text mining should be
combined with emergency plan compilation. Fixed " threshold strategy is used by traditional
DBSCAN, which would lead to the problem of cluster boundary wrong recognition. Improved
DBSCAN algorithm is introduced in this paper. Least Square Fit is taken to fit plans similarity
curve to find the best of initial " threshold. According to the initial " , a new strategy is used to
get dynamic " threshold to improve the precision and recall. The simulations results show that
the presented method is efficient for providing intelligent reference groups for government
staff.

목차

Abstract
 1. Introduction
 2. Algorithm
  2.1. Similarity of Plans
  2.2. Initialization of Neighborhood Threshold
  2.3. Improved DBSCAN Algorithm
 3. Experiment and Results Analysis
  3.1. Experiment Results
  3.2. Algorithm Analysis
 4. Conclusions
 Acknowledgements
 References

키워드

저자

• Huaiguang Wu [ School of Computer and Communication engineering, Zhengzhou University of Light Industry ]
• Qing Lin [ School of Computer and Communication engineering, Zhengzhou University of Light Industry ]
• Baohua Jin [ School of Computer and Communication engineering, Zhengzhou University of Light Industry ]
• Qi Liu [ College of Computer and Software, Nanjing University of Information Science and Technology ]

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