A Mathematical Approach to Investigate the Relationship between Association Memory and Latent Semantic Analysis in English and Chinese

Certain previous researches attempted to characterize how association memory works for items. LSA (latent semantic analysis) is usually showed highly related to forward association memory. A naive postulation would assume that the mechanisms for that relationship is mainly due to semantic similarity. The present work proposes that the linkage between LSA and association memory could be built on classical conditioning itself. The assumption is proven by analyzing the degree of divergence of association networks in the English and Chinese word database. Association memory of low frequency words is not found correlated to LSA in English, but correlated to scenario situations or proverbs. The results also showed that the reciprocal of divergence degree indicates the correlation of LSA and association memory. Finally, the mechanism of classical conditioning can be used to explain how the association memory is formed, and why the strength of constructing condition responses of classical conditioning from context is featured by LSA.

[1]  Ali A. Minai,et al.  Efficient associative memory using small-world architecture , 2001, Neurocomputing.

[2]  Masatoshi Tsuchiya,et al.  Context dependent class language model based on word co-occurrence matrix in LSA framework for speech recognition , 2008 .

[3]  S. Amari Statistical Neurodynamics — Associative Memory and Self-Organization , 1989 .

[4]  Richard M. Shiffrin,et al.  Word Association Spaces for Predicting Semantic Similarity Effects in Episodic Memory. , 2005 .

[5]  A. A. Mitchell,et al.  Models of Memory: Implications For Measuring Knowledge Structures , 1982 .

[6]  Neil Davey,et al.  High capacity, small world associative memory models , 2006, Connect. Sci..

[7]  Douglas L. Nelson,et al.  Entangled Associative Structures and Context , 2007, AAAI Spring Symposium: Quantum Interaction.

[8]  S.-i. Amari Statistical neurodynamics of various versions of correlation associative memory , 1988, IEEE 1988 International Conference on Neural Networks.

[9]  Peter W. Foltz,et al.  An introduction to latent semantic analysis , 1998 .

[10]  Thomas A. Schreiber,et al.  The University of South Florida free association, rhyme, and word fragment norms , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[11]  B. Babkin Conditioned Reflexes; an Investigation of the Physiological Activity of the Cerebral Cortex. , 1929 .

[12]  S. Nakagawa,et al.  Word Co-occurrence Matrix and Context Dependent Class in LSA based Language Model for Speech Recognition , 2009 .