DocumentCode
2823163
Title
A New Normalized Similarity for Discriminating Similar Documents
Author
Ji, Jeong-Hoon ; Ryu, Chang-Keon ; Woo, Gyun ; Cho, Hwan-Gue
Author_Institution
Dept. of Comput. Eng., Pusan Nat. Univ., Pusan
Volume
2
fYear
2008
fDate
2-4 Sept. 2008
Firstpage
108
Lastpage
113
Abstract
To find out similar document pairs from a set of documents, computing normalization similarities is inevitable because the sizes of documents are different from documents to documents. However, the normalized similarities proposed up to now are still unreliably sensitive to the size of programs compared. Due to this fact, most previously announced similarity detection tools have difficulties in determining the cutoff threshold to discriminate similar documents from a set of documents. In this paper, we propose a new normalized similarity based on Weibull distribution. To test the effectiveness of the new similarity measure, we applied it in detecting similar program pairs from a set of programs. According to the experiment, the new similarity measure showed very nice characteristics in discriminating the very similar program pairs from other pairs. Also, the proposed normalized similarity is effective in detecting similar documents written in natural languages.
Keywords
Weibull distribution; document handling; natural language processing; Weibull distribution; natural languages; normalization similarities; normalized similarities; plagiarism detection; similar document discrimination; similarity detection tools; Automatic programming; Biology computing; Clustering algorithms; Computer networks; Electronic mail; Information management; Natural languages; Plagiarism; Sequences; Weibull distribution; ICPC; Plagiarism Detection; Programming Contest; Weibull;
fLanguage
English
Publisher
ieee
Conference_Titel
Networked Computing and Advanced Information Management, 2008. NCM '08. Fourth International Conference on
Conference_Location
Gyeongju
Print_ISBN
978-0-7695-3322-3
Type
conf
DOI
10.1109/NCM.2008.189
Filename
4624126
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