Evaluation of Fingerprint Selection Algorithms for Two-Stage Plagiarism Detection
2021
Gints Jēkabsons

Generally, the process of plagiarism detection can be divided into two main stages: source retrieval and text alignment. The paper evaluates and compares effectiveness of five fingerprint selection algorithms used during the source retrieval stage: Every p-th, 0 mod p, Winnowing, Frequency-biased Winnowing (FBW) and Modified FBW (MFBW). The algorithms are evaluated on a dataset containing plagiarism cases in Bachelor and Master Theses written in English in the field of computer science. The best performance is reached by 0 mod p, Winnowing and MFBW. For these algorithms, reduction of fingerprint size from 100 % to about 20 % kept the effectiveness at approximately the same level. Moreover, MFBW sends overall fewer document pairs to the text alignment stage, thus also reducing the computational cost of the process. The software developed for this study is freely available at the author’s website http://www.cs.rtu.lv/jekabsons/.


Keywords
Document fingerprinting, fingerprint selection, indexing, plagiarism detection, text alignment, text reuse detection
DOI
10.2478/acss-2021-0022
Hyperlink
https://sciendo.com/article/10.2478/acss-2021-0022

Jēkabsons, G. Evaluation of Fingerprint Selection Algorithms for Two-Stage Plagiarism Detection. Applied Computer Systems, 2021, Vol. 26, No. 2, pp. 178-182. e-ISSN 2255-8691. Available from: doi:10.2478/acss-2021-0022

Publication language
English (en)
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