DocumentCode
2286431
Title
Original content extraction oriented to anti-plagiarism
Author
Shen, Yang ; Cheng, Ming ; Yao, Xing ; Wei, Wei
Author_Institution
Sch. of Inf. Manage., Wuhan Univ., Wuhan, China
fYear
2009
fDate
14-16 Sept. 2009
Firstpage
17
Lastpage
22
Abstract
In order to reduce the impact of inclusion of citations and references during the detection of plagiarism in academic theses, and extract the original content, the author created three ways to extract original content and remove the citation: 1) Removal of normative citations by symbol features; 2) removal tacit citations by Bayesian method based on the minimum risk and thesis structure; 3) removal common knowledge base on domain public knowledge base. The research results show that during the extraction of original content, the precision decreases as the risk coefficient increases, while the recall rate increases with the risk coefficient. When the risk coefficient is 60, the whole performance achieves the optimum. Plagiarism detection after extracting the original content presents a fault rate decrease from 9.09% to 4.52%.
Keywords
belief networks; citation analysis; information retrieval; Bayesian method; content extraction; normative citations removal; plagiarism detection; removal tacit citations; Conference management; Content management; Data mining; Engineering management; Knowledge management; Plagiarism; Prototypes; Risk management; Software libraries; Web pages; Beyes; citation removal; content extraction; plagiarism; thesis structure;
fLanguage
English
Publisher
ieee
Conference_Titel
Management Science and Engineering, 2009. ICMSE 2009. International Conference on
Conference_Location
Moscow
Print_ISBN
978-1-4244-3970-6
Electronic_ISBN
978-1-4244-3971-3
Type
conf
DOI
10.1109/ICMSE.2009.5317530
Filename
5317530
Link To Document