Plagiarism detection using semantic analysis
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2010.
| Huvudupphovsman: | |
|---|---|
| Övriga upphovsmän: | |
| Materialtyp: | Lärdomsprov |
| Språk: | English |
| Publicerad: |
BRAC University
2011
|
| Ämnen: | |
| Länkar: | http://hdl.handle.net/10361/741 |
| id |
10361-741 |
|---|---|
| record_format |
dspace |
| spelling |
10361-7412022-01-26T10:13:19Z Plagiarism detection using semantic analysis Shams, Khalid Rhaman, Md. Khalilur Department of Computer Science and Engineering, BRAC University Computer science and engineering This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2010. Cataloged from PDF version of thesis report. Includes bibliographical references (page 24). Plagiarism in the sense of “theft of intellectual property” has been around for as long as humans have produced work of art and research. However, easy access to the Web, large databases, and telecommunication in general, has turned plagiarism into a serious problem for publishers, researchers and educational institutions. Plagiarism detection is a technique to find out the theft of scientific paper, literary works, source code etc. An existing method to find out similar documents is to use Self-Organizing Maps (SOMs)1. But there are some efficiency challenges like processing time arise in creating these maps. To facilitate recognition of plagiarism, Researchers2,3 at MIT used a set of low-level syntactic structures to evaluate content and expression in a document. However, we think only syntactic structures may not give optimal output in detecting plagiarism because it may not always detect the insight meaning. To detect plagiarism, our idea is to propose a synonym and antonym based framework to evaluate text similarity with respect to the similarity of content between the original and plagiarized document. Rather using low-level syntactic structures i.e. Context-free Grammar (CFG)4, synonymic features of sentences which we think will improve the overall combat against plagiarism. Shams, Khalid 36 pages B. Computer Science and Engineering 2011-01-26T08:44:10Z 2011-01-26T08:44:10Z 2010 2010-04 Thesis ID 02201081 http://hdl.handle.net/10361/741 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 36 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Computer science and engineering |
| spellingShingle |
Computer science and engineering Shams, Khalid Plagiarism detection using semantic analysis |
| description |
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2010. |
| author2 |
Rhaman, Md. Khalilur |
| author_facet |
Rhaman, Md. Khalilur Shams, Khalid |
| format |
Thesis |
| author |
Shams, Khalid |
| author_sort |
Shams, Khalid |
| title |
Plagiarism detection using semantic analysis |
| title_short |
Plagiarism detection using semantic analysis |
| title_full |
Plagiarism detection using semantic analysis |
| title_fullStr |
Plagiarism detection using semantic analysis |
| title_full_unstemmed |
Plagiarism detection using semantic analysis |
| title_sort |
plagiarism detection using semantic analysis |
| publisher |
BRAC University |
| publishDate |
2011 |
| url |
http://hdl.handle.net/10361/741 |
| work_keys_str_mv |
AT shamskhalid plagiarismdetectionusingsemanticanalysis |
| _version_ |
1814308196343349248 |