Salton was perhaps most well known for developing the now widely used vector space model for Information Retrieval. In this model, both documents and queries are represented as vectors of term counts, and the similarity between a document and a query is given by the cosine between the term vector and the document vector. In this paper, he also introduced TF-IDF, or term-frequency-inverse-document frequency, a model in which the score of a term in a document is the ratio of the number of terms in that document divided by the frequency of the number of documents in which that term occurs. (The concept of inverse document frequency, a measure of specificity, had been introduced in 1972 by Karen Sparck-Jones.) Later in life, he became interested in automatic text summarization and analysis, as well as automatic hypertext generation. He published over 150 research articles and 5 books during his life.