Latent Semantic Indexing is an Optimal Special Case of Multidimensional Scaling

by: Brian T Bartell, Garrison W Cottrell, Richard K Belew

(1992), pp. 161-167.

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Abstract

Latent Semantic Indexing (LSI) is a technique for representing documents, queries, and terms as vectors in a multidimensional real-valued space. The representations are approximations to the original term space encoding, and are found using the matrix technique of Singular Value Decomposition. In comparison, Multidimensional Scaling (MDS) is a class of data analysis techniques for representing data points as points in a multidimensional real-valued space. The objects are represented so that...

@inproceedings{citeulike:460245, abstract = {Latent Semantic Indexing (LSI) is a technique for representing documents, queries, and terms as vectors in a multidimensional real-valued space. The representations are approximations to the original term space encoding, and are found using the matrix technique of Singular Value Decomposition. In comparison, Multidimensional Scaling (MDS) is a class of data analysis techniques for representing data points as points in a multidimensional real-valued space. The objects are represented so that...}, author = {Bartell, Brian T. and Cottrell, Garrison W. and Belew, Richard K. }, booktitle = {Research and Development in Information Retrieval}, citeulike-article-id = {460245}, pages = {161--167}, posted-at = {2007-09-02 18:06:38}, priority = {2}, title = {Latent Semantic Indexing is an Optimal Special Case of Multidimensional Scaling}, url = {http://citeseer.ist.psu.edu/bartell92latent.html}, year = {1992} }

RIS record

TY - CONF ID - citeulike:460245 L3 - citeulike-article-id:460245 TI - Latent Semantic Indexing is an Optimal Special Case of Multidimensional Scaling T2 - Research and Development in Information Retrieval SP - 161 EP - 167 N2 - Latent Semantic Indexing (LSI) is a technique for representing documents, queries, and terms as vectors in a multidimensional real-valued space. The representations are approximations to the original term space encoding, and are found using the matrix technique of Singular Value Decomposition. In comparison, Multidimensional Scaling (MDS) is a class of data analysis techniques for representing data points as points in a multidimensional real-valued space. The objects are represented so that... AU - Bartell, Brian AU - Cottrell, Garrison AU - Belew, Richard PY - 1992/// UR - http://citeseer.ist.psu.edu/bartell92latent.html ER -

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