Application of cosine similarity to detect plagiarism
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