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A study was conducted to test the effectiveness of similarity detection software in a higher education setting. One part of the study assigned one group of students to write a paper. These students were first educated about plagiarism and informed that their work was to be run through a content similarity detection system.
Bibliographic coupling occurs when two works reference a common third work in their bibliographies. It is an indication that a probability exists that the two works treat a related subject matter. [1] Two documents are bibliographically coupled if they both cite one or more documents in common. The "coupling strength" of two given documents is ...
Co-citation is the frequency with which two documents are cited together by other documents. [1] If at least one other document cites two documents in common, these documents are said to be co-cited. The more co-citations two documents receive, the higher their co-citation strength, and the more likely they are semantically related. [1]
This prevents one student from using another student's paper, by identifying matching text between papers. In addition to student papers, the database contains a copy of the publicly accessible Internet, with the company using a web crawler to continually add content to Turnitin's archive. It also contains commercial and/or copyrighted pages ...
SimRank is a general approach that exploits the object-to-object relationships found in many domains of interest. On the Web, for example, two pages are related if there are hyperlinks between them. A similar approach can be applied to scientific papers and their citations, or to any other document corpus with cross-reference information. In ...
The resultant SSIM index is a decimal value between -1 and 1, where 1 indicates perfect similarity, 0 indicates no similarity, and -1 indicates perfect anti-correlation. For an image, it is typically calculated using a sliding Gaussian window of size 11x11 or a block window of size 8×8.
This value is 0 when the two sets are disjoint, 1 when they are equal, and strictly between 0 and 1 otherwise. Two sets are more similar (i.e. have relatively more members in common) when their Jaccard index is closer to 1. The goal of MinHash is to estimate J(A,B) quickly, without explicitly computing the intersection and union.
Direct evidence of actual copying by a defendant rarely exists, so plaintiffs must often resort to indirectly proving copying. [1] [page needed] Typically, this is done by first showing that the defendant had access to the plaintiff's work and that the degree of similarity between the two works is so striking or substantial that the similarity could only have been caused by copying, and not ...
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