Plagiarism is a problem with far-reaching consequences for the sciences. However, even today’s best software-based systems can only reliably identify copy & paste plagiarism. Disguised plagiarism forms, including paraphrased text, cross-language plagiarism, as well as structural and idea plagiarism often remain undetected. This weakness of current systems results in a large percentage of scientific plagiarism going undetected. Bela Gipp provides an overview of the state-of-the art in plagiarism detection and an analysis of why these approaches fail to detect disguised plagiarism forms. The author proposes Citation-based Plagiarism Detection to address this shortcoming. Unlike character-based approaches, this approach does not rely on text comparisons alone, but analyzes citation patterns within documents to form a language-independent "semantic fingerprint" for similarity assessment. The practicability of Citation-based Plagiarism Detection was proven by its capability to identify so-far non-machine detectable plagiarism in scientific publications.

• Paperback: 350 pages
• Publisher: Springer Vieweg; 2014 edition (July 31, 2014)
• Language: English
• ISBN-10: 3658063939
• ISBN-13: 978-3658063931
• Product Dimensions: 5.8 x 0.8 x 8.3 inches
• Shipping Weight: 1 pounds
• http://www.amazon.com/Citation-based-Plagiarism-Detection-Detecting-Cross-language/dp/3658063939/ref=sr_1_1_twi_1?ie=UTF8&qid=1415850586&sr=8-1&keywords=Citation-based+Plagiarism+Detection%3A+Detecting+Disguised+and+Cross-language+Plagiarism+using+Citation+Pattern+Analysis