Integrating syntax‐semantic‐based text analysis with structural and citation information for scientific plagiarism detection

K Vani and Deepa Gupta

Journal of the Association for Information Science & Technology, 2018, vol. 69, issue 11, 1330-1345

Abstract: The objective of the work is to explore the potency of integrating structural and citation information with effective syntax‐semantic text‐based analysis for scientific plagiarism detection. One of the major limitations in today's plagiarism checkers is their sole dependence on text‐based detection, where they ignore the citation and structural information. Further, the text‐based detection approaches that they employ usually fail to trace out intelligent manipulations. In the proposed work, a plagiarism detection system is presented that employs the effective coupling of various modules, namely, logical structure classifications and citation parsing, two‐stage candidate document selections, syntax‐semantic‐based exhaustive passage level analysis with plagiarism analysis using structural and citation information. Further, a new plagiarism score, namely, weighted overall similarity index is proposed, opposed to the general plagiarism scores. The proposed approach is evaluated on the data set created by Alzahrani et al. (), which contains scientific publications imposed with various plagiarism complexities. Comparison of the final system results is done against a potential baseline approach. The proposed approach exhibits considerable improvement over the comparative baseline, and hence reflects the potency of syntax‐semantic text‐based analysis with structural and citation information.

Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1002/asi.24027

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jinfst:v:69:y:2018:i:11:p:1330-1345

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=2330-1635

Access Statistics for this article

More articles in Journal of the Association for Information Science & Technology from Association for Information Science & Technology
Bibliographic data for series maintained by Wiley Content Delivery ().