Accession Number:

AD1158406

Title:

Distributed Vector Representations of Words in the Sigma Cognitive Architecture

Descriptive Note:

[Technical Report, Research Paper]

Corporate Author:

UNIVERSITY OF SOUTHERN CALIFORNIA LOS ANGELES

Report Date:

2014-01-01

Pagination or Media Count:

12

Abstract:

Recently reported results with distributed-vector word representations in natural language processing make them appealing for incorporation into a general cognitive architecture like Sigma. This paper describes a new algorithm for learning such word representations from large, shallow information resources, and how this algorithm can be implemented via small modifications to Sigma. The effectiveness and speed of the algorithm are evaluated via a comparison of an external simulation of it with state-of-the-art algorithms. The results from more limited experiments with Sigma are also promising, but more work is required for it to reach the effectiveness and speed of the simulation.

Descriptors:

Subject Categories:

  • Numerical Mathematics

Distribution Statement:

[A, Approved For Public Release]