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Conference papers
Information Theoretical and Statistical Features for Intrinsic Plagiarism Detection
Abstract : In this paper we present some information theoretical and statistical features including function word skip n-grams for detecting plagiarism intrinsically. We train a binary classifier with different feature sets and observe their performances. Basically, we propose a set of 36 features for classifying plagiarized and non-plagiarized texts in suspicious documents. Our experiment finds that entropy, relative entropy and correlation coefficient of function word skip n-gram frequency profiles are very effective features. The proposed feature set achieves F-Score of 85.10%.
https://hal.archives-ouvertes.fr/hal-01617333
Contributor : Rashedur Rahman <>
Submitted on : Monday, October 16, 2017 - 2:50:36 PM
Last modification on : Monday, February 10, 2020 - 6:14:06 PM
Contributor : Rashedur Rahman <>
Submitted on : Monday, October 16, 2017 - 2:50:36 PM
Last modification on : Monday, February 10, 2020 - 6:14:06 PM
