Information Retrieval using a Singular Value Decomposition Model of Latent Semantic Structure - Furnas, George W.; Dumais, Susan; Landauer, Thomas K.; Harshman, Richard A.; Streeter, Lynn A.; Lochbaum, Karen E. (Proceedings of SIGIR 1998, 1998)
In a new method for automatic indexing and retrieval, implicit higher-order structure in the association of terms with documents is modeled to improve estimates of term-document association, and therefore the detection of relevant documents on the basis of terms found in queries. Singular-value decomposition is used to decompose a large term by document matrix into 50 to 150 orthogonal factors from which the original matrix can be approximated by linear combination; both documents and terms are represented as vectors in a 50- to 150- dimensional space. Queries are represented as pseudo-documents vectors formed from weighted combinations of terms, and documents are ordered by their similarity to the query. Initial tests find this automatic method very promising.
SIGIR Test-of-Time Award