dc.contributor.author |
Amaranathan, Anojini |
|
dc.date.accessioned |
2021-07-27T04:20:14Z |
|
dc.date.available |
2021-07-27T04:20:14Z |
|
dc.date.issued |
2020 |
|
dc.identifier.citation |
Amaranathan, Anojini (2020) iPlagiDetect: Smart Plagiarism Detector, BEng. Dissertation Informatics Institute of Technology |
en_US |
dc.identifier.other |
2016437 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/609 |
|
dc.description.abstract |
Plagiarism is a serious problem in this technological era where finding and accessing information has become easy through the World Wide Web. Plagiarism is defined as presenting someone else idea or work, intentionally or unintentionally as your own without giving proper acknowledgement to the author. It is immoral to use the ideas, work, and words of someone without giving acknowledgement to them. A vast number of researches are going on the field of plagiarism detection. This project focus on plagiarism detection in textual images where the author proposes a method to detect mosaic plagiarism in textual images using a semantic-based approach. Mosaic plagiarism is when the words of the original author were changed by synonyms but keeping the structure of the sentence as same. The proposed system will enhance the ability of currently available system for plagiarism detection. |
en_US |
dc.subject |
Optical Character Recognition |
en_US |
dc.subject |
Natural language processing |
en_US |
dc.subject |
Plagiarism Detection |
en_US |
dc.subject |
Semantic similarity |
en_US |
dc.title |
iPlagiDetect: Smart Plagiarism Detector |
en_US |
dc.type |
Thesis |
en_US |