Cogprints
Login | Create Account

Connectionist Taxonomy Learning

Frey, Miloslaw (2004) Connectionist Taxonomy Learning. (Unpublished)

Full text available as:

[img]
Preview
PDF
76Kb

Abstract

The paper at hand describes an approach to automatise the creation of a class taxonomy. Information about objects, e.g. "a tank is armored and moves by track", but no prior knowledge about taxonomy structure is presented to a connectionist system which organizes itself by means of activation spreading (McClelland and Rumelhart, 1981) and weight adjustments. The resulting connectionist network has a form of a taxonomy sought-after.

Item Type:Other
Subjects:Computer Science > Language
Linguistics > Semantics
Computer Science > Machine Learning
Computer Science > Neural Nets
ID Code:3943
Deposited By:Frey, Miloslaw
Deposited On:20 Nov 2004
Last Modified:12 Sep 2007 17:54

References in Article

Select the SEEK icon to attempt to find the referenced article. If it does not appear to be in cogprints you will be forwarded to the paracite service. Poorly formated references will probably not work.

A. Gomez-Perez and D. Manzano-Macho. A Survey of Ontology Learning Methods and Techniques. Deliverable 1.5, OntoWeb Project, 2003.

J. L. McClelland and D. E. Rumelhart. An interactive activation model of context effects in letter perception: Part 1. An account of basic findings. Psychological Review, 88:375-407, 1981.

E. Rosch. Family resemblance: Studies in the internal structure of categories. Cognitive Psychology, 7:573-605, 1975.

Metadata

Repository Staff Only: item control page

Cogprints is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.