neural networks research group
DISCERN is a large, modular neural network system for reading, paraphrasing and answering questions about stereotypical (script-based) stories. A precis of this book and a short summary paper should give you a quick overview of this research. To get an idea what the DISCERN programs are like (without having to first port them), take a look at the on-line demo. It runs remotely on cascais.cs.utexas.edu, with graphics display on your X11 screen. The DISCERN software consists of four components: 1. PROC for training and testing the backpropagation-based processing modules (for parsing, generation, and question answering), 2. HFM for training and testing the hierarchical feature maps that form the basis for the episodic memory, 3. DISLEX for training and testing the lexicon (lexical and semantic feature maps and associative connections between them), and 4. DISCERN, which is the integrated complete story processing model put together from the final results of the above three programs. Comments to firstname.lastname@example.org.
Ralph E. Hoffman
ralph hoffman [at] yale edu
risto [at] cs utexas edu
Neural Network Models of Schizophrenic Language
Processing Script-Based Stories: The DISCERN System
1990 - 1994
Storing Information on Maps: The Trace Feature Map Model
1990 - 1994
Modeling Acute and Compensated Language Disturbance in Schizophrenia
Uli Grasemann, Ralph Hoffman and Risto Miikkulainen
Proceedings of the 33rd Annual Meeting of the Cognitive Science Society
Using Computational Patients to Evaluate Illness Mechanisms in Schizophrenia
Ralph E. Hoffman, Uli Grasemann, Ralitza Gueorguieva, Donald Quinlan, Douglas Lane, and Risto Miikku...
, 69:997--1005, 2011.
A Subsymbolic Model of Language Pathology in Schizophrenia
Uli Grasemann, Risto Miikkulainen, Ralph Hoffman
Proceedings of the 29th Annual Conference of the Cognitive Science Society
, 311-316, Hill...
Text and Discourse Understanding: The DISCERN System
In R. Dale, H. Moisl and H. Somers, editors,
A Handbook of Natural Language Processing: Technique...
Script-Based Inference And Memory Retrieval In Subsymbolic Story Processing
Integrated Connectionist Models: Building AI Systems on Subsymbolic Foundations
Honavar, V., and Uhr, L., editors,
Artificial Intelligence and Neural Networks: Steps Toward Prin...
Subsymbolic Natural Language Processing: An Integrated Model Of Scripts, Lexicon, And Memory
, Cambridge, MA, 1993. MIT Press.
DISCERN: A Distributed Artificial Neural Network Model Of Script Processing And Memory
PhD Thesis, University of California, 1990. 334.
A Subsymbolic Model of Schizophrenic Language
Areas of Interest
Natural Language Processing (Cognitive)
Brain and Cognitive Disorders