원문정보
보안공학연구지원센터(IJDTA)
International Journal of Database Theory and Application
Vol.5 No.4
2012.12
pp.23-32
피인용수 : 0건 (자료제공 : 네이버학술정보)
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
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
저자정보
참고문헌
자료제공 : 네이버학술정보