Application of cosine similarity to detect plagiarism Can anyone tell me how using cosine similarity to see the correlation between two documents actually shows you if someone is plagiarising the other? I understand how cosine similarity works but don't understand how using this shows how closely related they are when the cosine deals with vectors and angles. How can this relate to a document?
Usually this would be used in conjunction with a bag of words model. You need to convert each document to a vector where the length of the vector is the number of words in the vocabulary. The entries in the vector correspond to the number of occurrences of each vocabulary word in the document. You can apply cosine similarity to these document vectors.

You should consider using tf-idf weighting to make sure that a small set of very common words doesn't end up dominating the distance computation. https://en.wikipedia.org/wiki/Tf%E2%80%93idf