PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Reducing the Plagiarism Detection Search Space on the basis of the Kullback-Leibler Distance
Alberto Barrón Cedeño, Paolo Rosso and José Miguel Benedí
In: 10th International Conference on Computational Linguistics and Intelligent Text Processing(2009).

Abstract

Automatic plagiarism detection considering a reference cor- pus compares a suspicious text to a set of original documents in order to relate the plagiarised fragments to their potential source. Publications on this task often assume that the search space (the set of reference documents) is a narrow set where any search strategy will produce a good output in a short time. However, this is not always true. Reference corpora are often composed of a big set of original documents where a simple exhaustive search strategy becomes practically impossible. Before carrying out an exhaustive search, it is necessary to reduce the search space, represented by the documents in the reference corpus, as much as possible. Our experiments with the METER corpus show that a previous search space reduction stage, based on the Kullback-Leibler symmetric distance, reduces the search process time dramatically. Ad- ditionally, it improves the Precision and Recall obtained by a search strategy based on the exhaustive comparison of word n-grams.

EPrint Type:Conference or Workshop Item (Oral)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
Information Retrieval & Textual Information Access
ID Code:5709
Deposited By:Alfons Juan
Deposited On:08 March 2010