%0 Journal Article %1 furnas_information_2017 %A Furnas, George W. %A Deerwester, Scott %A Dumais, Susan T. %A Landauer, Thomas K. %A Harshman, Richard A. %A Streeter, Lynn A. %A Lochbaum, Karen E. %D 2017 %J SIGIR Forum %K latent_semantic_indexing %P 90--105 %T Information retrieval using a singular value decomposition model of latent semantic structure %V 51 %X 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.

@article{furnas_information_2017, abstract = {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.}, added-at = {2018-11-04T17:00:37.000+0100}, author = {Furnas, George W. and Deerwester, Scott and Dumais, Susan T. and Landauer, Thomas K. and Harshman, Richard A. and Streeter, Lynn A. and Lochbaum, Karen E.}, biburl = {https://www.bibsonomy.org/bibtex/2fe38789ba93a161b22e92f282a6e3ba8/lepsky}, interhash = {63cf71136321c4346d11c5494696feb4}, intrahash = {fe38789ba93a161b22e92f282a6e3ba8}, issn = {01635840}, journal = {SIGIR Forum}, keywords = {latent_semantic_indexing}, month = jul, pages = {90--105}, timestamp = {2018-11-07T09:16:24.000+0100}, title = {Information retrieval using a singular value decomposition model of latent semantic structure}, volume = 51, year = 2017 }