Information retrieval and categorisation using a cell assembly network

Article

Huyck, C. and Orengo, V. 2005. Information retrieval and categorisation using a cell assembly network. Neural Computing and Applications. 14 (4), pp. 282-289. https://doi.org/10.1007/s00521-004-0464-6
TypeArticle
TitleInformation retrieval and categorisation using a cell assembly network
AuthorsHuyck, C. and Orengo, V.
Abstract

In this paper, CAs are applied to practical data mining tasks. The first is a standard categorisation task, the congressional voting task. The learning mechanisms allow this real world problem to be easily solved. An information retrieval task is also run. A straight forward neuron per word mechanism is used to represent documents. When a document is presented, all the neurons associated with each word are fired. The retrieval results are on par with existing IR methods. This shows the immediate applicability of the CA concept. CAs also provide a theoretical foundation for the long term development of cognitive architectures.

Keywordsinformation retrieval; categorisation; neural network; cell assembly; Hebbian learning
Research GroupArtificial Intelligence group
PublisherSpringer
JournalNeural Computing and Applications
ISSN0941-0643
Publication dates
Print30 Mar 2005
Publication process dates
Deposited17 Oct 2008
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1007/s00521-004-0464-6
Web of Science identifierWOS:000232985200002
LanguageEnglish
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