Internet is a path of information, lots and lots of information. People can get their own ideas on everything they want to write and know. But the biggest problem now is how to identify plagiarism. Plagiarism is now very rampant, streaming like wild fires in the internet. Articles may have different titles or different in some words but still it delivers the same thought- let us say it was just customized or paraphrased.
The big maze now is how the
researchers will uncover the copycat study or article.
Dallas Research group provides some new solutions on this problem--the cut/copy and paste documents which is unethical practice in doing documentations.
This piracy leads to be a big problem especially in the medicine. "In medicine, researchers and clinicians rely on research, and so this has high potential for doing harm," said Harold "Skip" Garner, a professor of biochemistry and internal medicine at medical center and one of the project's co-leaders.
Garner and his colleagues originally devised their program, named eTBLAST, for biomedical researchers. "In this program you can check the originality of your idea and identify your competitors or collaborators" Garner said. Last year, their team select summaries from the MEDLINE database and put this eTBLAST to the test. They quickly discovered that their code works very well.
eTBLAST works...
- eTBLAST compares the wording of other summaries in the database and retrieves the top 400 to 1,000 matches.
- The algorithms then go sentence by sentence, scanning for match works. The program not only matches alternate spellings of the same word but also pick out synonyms of the words.
With the help of federal
Office of Research Integrity, Garner's group conducted a more systematic review
on the results of some medical research. The results were published in the
journal Bioinformatics and follow-up commentary in the "Nature" journal. They
found out that the potential plagiarism represented about 0.04 percent of MEDLINE's database or roughly 6,700 cases in all. With this, 1.3 percent of database's documents
were represented by similar studies re-published by the same authors. The group aptly flagged more the 71,000 suspicious pairs as a whole.
So, cheaters beware! This unethical act will lead you to trouble...