Word frequency effects in high-dimensional co-occurrence models: A new approach
Related Experiment Video
Updated: Jul 20, 2026

Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
1Department of Psychology, University of Alberta, Edmonton, Alberta, Canada. cyrus.shaoul@ualberta.ca
Abstract:
The HAL (hyperspace analog to language) model of lexical semantics uses'global word co-occurrence from a large corpus of text to calculate the distance between words in co-occurrence space. We have implemented a system called HiDEx (High Dimensional Explorer) that extends HAL in two ways: It removes unwanted influence of orthographic frequency from the measures of distance, and it finds the number of words within a certain distance of the word of interest (NCount, the number of neighbors). These two changes to the HAL model produce measures of word neighborhood density that are reliably predictive of human lexical decision reaction times.
Related Concept Videos
Expected Frequencies in Goodness-of-Fit Tests
Causes of Similarity-Dissimilarity Effect
Friedman Two-way Analysis of Variance by Ranks
Collisions in Multiple Dimensions: Introduction
Determination of Expected Frequency
Per-Unit Sequence Models
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
