Unit RR, Part B1: Basic Vector Space Model

Vector Space

• Model of feature space as a t-dimensional vector space
• Each dimension represents a term or concept (found in documents)
• Each document and query is represented as a point in the space
• Groups of documents are represented by their centroid point

Vector Similarity

• Similarity between two points is measured by the cosine of the angle between their two vectors.
• That is computed as the inner product of the two vectors, normalized (divided) by the products of the vector lengths (square root of the sums of squares).