  Plagiarism is known as illegal use of others' part of work or whole work as
one's own in any field such as art, poetry, literature, cinema, research and
other creative forms of study. Plagiarism is one of the important issues in
academic and research fields and giving more concern in academic systems. The
situation is even worse with the availability of ample resources on the web.
This paper focuses on an effective plagiarism detection tool on identifying
suitable intra-corpal plagiarism detection for text based assignments by
comparing unigram, bigram, trigram of vector space model with cosine similarity
measure. Manually evaluated, labelled dataset was tested using unigram, bigram
and trigram vector. Even though trigram vector consumes comparatively more
time, it shows better results with the labelled data. In addition, the selected
trigram vector space model with cosine similarity measure is compared with
tri-gram sequence matching technique with Jaccard measure. In the results,
cosine similarity score shows slightly higher values than the other. Because,
it focuses on giving more weight for terms that do not frequently exist in the
dataset and cosine similarity measure using trigram technique is more
preferable than the other. Therefore, we present our new tool and it could be
used as an effective tool to evaluate text based electronic assignments and
minimize the plagiarism among students.
