| Popis: |
With high use of internet technology worldwide, the growth of data availability is also growing rapidly. With the availability of ready data, it attracts few people to steal the data and use it as it is generated by them. Mostly it is found in the higher education sector where students and teachers use the existing information and commit plagiarism. It is an important task to perform Plagiarism detection at various levels to control the theft of data and maintain the novelty of the source of information. To do this, the research has already been started for many years. Over the period of time many tools and techniques have been developed to detect plagiarism at various levels. Still there are many issues present for detecting plagiarism because of many reasons such as language, availability of data sets, availability of highly sophisticated algorithms etc. There is much research performed on detection of Plagiarism based on world level, also called as syntactic level as it is based on only words and their forms within the text. But there is less research done for detection of plagiarism at semantic level [10]. Due to unavailability of Corpus, algorithms, techniques etc. the semantic level plagiarism detection is becoming a tedious task. In this paper we are presenting different available tools and techniques which are used for plagiarism detection. The detailed taxonomy and various methodologies for identification of plagiarised contents has been explained in detail. |
