Within Information Retrieval each document in a set can be represented as a point in high-dimensional vector space, this representation is called the vector space model. Information Retrieval queries are also represented as vectors in the same vector space; these are then used in conjunction with the document vectors to find relevant documents. The two vectors are compared and the documents with a higher document-query similarity are ranked higher in terms of relevance. There are a variety of techniques that can be used to compare the two vectors; the most frequently used method for the vector space model is the Cosine Coefficient, which calculates the angle between the two vectors and produces a value between 0 and 1.