An improved online plagiarism detection approach for semantic analysis using custom search engine

Plagiarism is increasing in every field day by day such as plagiarism in music, paintings, maps, technical articles and drawings, academics etc. Due to use of smart phones and advancement of information in world increased availability of information openly, leads to plagiarism of data. Plagiarism refers to stealing and passing off another words or ideas as one's own. Plagiarism can be of different types. Plagiarism Detection is performed by matching string of one document with another document. Matching can be performed in two ways intra (to detect plagiarism within small organization like college) and extra-corpal (to detect plagiarism globally through web). This paper discuss extra-corpal semantic matching using custom search engine following crawlingprocess. By using custom search engine, we have accessed data globally. Custom search engine gives various links related to words i.e. Source of that word and then proposed method perform semantic analysis. For detecting plagiarism, existing system focus on keywords but fail to detect plagiarism using semantic web. We have proposed new system for detecting the plagiarism globally by custom search engine using semantic technology. After the implementation of this algorithm, fast and accurate system for plagiarism detection has been developed.