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Updated: Jun 4, 2026

A Semantic Priming Event-related Potential (ERP) Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder

A Semantic Priming Event-related Potential (ERP) Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder

Published on: April 12, 2018

Large-scale latent semantic analysis.

Andrew McGregor Olney¹

¹Institute for Intelligent Systems, 365 Innovation Drive, Suite 303, Memphis, TN 38152, USA. aolney@memphis.edu

Behavior Research Methods

|February 9, 2011

Summary

This summary is machine-generated.

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Latent semantic analysis (LSA) uses singular value decomposition (SVD) to understand word meaning. A new SVD algorithm, LANSE, efficiently processes large LSA matrices on standard hardware.

Area of Science:

Computational linguistics
Natural Language Processing
Statistical analysis

Background:

Latent semantic analysis (LSA) is a key statistical method for determining semantic similarity.
LSA involves creating a word frequency matrix and reducing its dimensionality via singular value decomposition (SVD).

Purpose of the Study:

To present LANSE, a novel SVD algorithm optimized for LSA.
To enable processing of extremely large matrices for LSA using conventional hardware.

Main Methods:

Development of the LANSE SVD algorithm.
Application of LANSE to process large-scale word frequency matrices for LSA.

Main Results:

LANSE successfully processes extremely large matrices.

Related Experiment Videos

Last Updated: Jun 4, 2026

A Semantic Priming Event-related Potential (ERP) Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder

A Semantic Priming Event-related Potential (ERP) Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder

Published on: April 12, 2018

The algorithm is designed for efficient LSA on off-the-shelf computer hardware.

Conclusions:

LANSE provides an efficient solution for large-scale LSA.
This advancement facilitates deeper semantic analysis with accessible computational resources.