UTCS Artificial Intelligence
Learning Word Meanings: The FGREP Method
Active from 1987 - 1994
With FGREP, distributed representations for words are developed as part of the task. The representations reflect how the words are used in the task, and in this sense, also stand for the meanings of the words: words that are used the same way have similar representations. FGREP representations lead to good generalization and robustness under noise, and the method frees the system designer from having to encode the representations by hand. FGREP is used for example in DISCERN, SPEC, DISLEX, and the semantic disambiguation projects described on this page.
risto [at] cs utexas edu
Lappoon R. Tang
ltang [at] utb edu
Natural Language Processing With Modular PDP Networks And Distributed Lexicon
Risto Miikkulainen and Michael G. Dyer
Natural Language Processing (Cognitive)
The FGREPNET package contains the C-code and data for training and testing an FGREP network in developing distributed re...