NDLI: Web Based Cross Language Semantic Plagiarism Detection

Content Provider	IEEE Xplore Digital Library
Author	Kent, C.K. Salim, N.
Copyright Year	2011
Abstract	As the Internet help us cross language and cultural border and with different types of translation tools, cross language plagiarism is bound to rise. Besides that, semantic plagiarism, where the student reconstructs the sentence or changes some terms into its corresponding synonyms, also raises concerns in the academic field. Both of this plagiarism is hardly detected due to the difference in their fingerprints. Plagiarism detection tools available are not capable to detect such plagiarism cases. In this research, we propose a new approach in detecting both cross language and semantic plagiarism. We consider Bahasa Melayu as the input language of the submitted document and English as a target language of similar, possibly plagiarised documents. In this system we shorten the query document by utilising fuzzy swarm-based summarisation approach. Our point of view is that using the summary will give us the most important keywords in the document. Input summary documents are translated into English using Google Translate Application Programming Interface (API) before the words are stemmed and the stop words are removed. Tokenized documents are sent to the Google AJAX Search API to detect similar documents throughout the World Wide Web. We integrate the use of Stanford Parser and Word Net to determine the semantic similarity level between the suspected documents with candidate source documents. Stanford parser assigns each terms in the sentence to their corresponding roles such as Nouns, Verbs and Adjectives. Based on these roles, we represent each sentence in a predicate form and similarity is measured based on those predicates using information content value from Word Net taxonomy. Our testing dataset is built up from two sets of Malay documents which are produced based on different plagiarism techniques. The result of our proposed semantic based similarity measurement shows that it can achieve higher precision, recall and F-Measure compared to the conventional Longest Common Subsequence (LCS) approach.
Starting Page	1096
Ending Page	1102
File Size	339455
Page Count	7
File Format	PDF
ISBN	9781467300063
DOI	10.1109/DASC.2011.180
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-12
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Google semantic Plagiarism Weapons Semantics Taxonomy fuzzy swarm based summarization cross language Fingerprint recognition plagiarism detection Testing
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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