Document ranking refers to the methodology that ranks the returned documents with respect to a given query in a proper order. In general, document ranking is based on a weighting model, which assigns a relevance score to each document, and ranks the documents accordingly. Many weighting models have been developped in the past. Following is a list of popular weighting models:

G. Salton and A. Wong and C.S. Yang. A Vector Space Model for Information Retrieval. Journal of American Society for Information Retrieval. Volume 18(11), pages 613 - 620, November 1975.

[WWW] Terrier provides implementations of BM25, DivergenceFromRandomness models and Ponte & Croft's approach to language modelling.

last edited 2005-05-02 20:28:17 by BenHe