원문정보
보안공학연구지원센터(IJSIA)
International Journal of Security and Its Applications
Vol.10 No.11
2016.11
pp.67-78
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Fingerprint feature-based text copy detection can rapidly identify the plagiarism, but suffers from the excessive fingerprint density. To resolve the problem, we propose a fingerprint feature extraction algorithm based on the optimal decision, combined with Winnowing algorithm and optimal decision model, and it can extract fingerprint feature from the hash values in the sliding window. The experimental results demonstrate that our algorithm can reduce the fingerprint density when the windows’ fingerprint feature is too adjacent, and the selected fingerprints can represent the text feature on the premise of the accuracy of the text copy and the algorithm.
목차
Abstract
1. Introduction
2. Optimal Decision-based Fingerprint Feature Extraction
2.1. Optimal Decision Model
2.2. Algorithm Description
2.3. Fingerprint Density Analysis
3. Experimental Results and Analysis
3.1. Data-sets and Evaluation Criteria
3.2. Experimental Results and Analysis
4. Conclusions
References
1. Introduction
2. Optimal Decision-based Fingerprint Feature Extraction
2.1. Optimal Decision Model
2.2. Algorithm Description
2.3. Fingerprint Density Analysis
3. Experimental Results and Analysis
3.1. Data-sets and Evaluation Criteria
3.2. Experimental Results and Analysis
4. Conclusions
References
저자정보
참고문헌
자료제공 : 네이버학술정보
