Modeling a User's Domain Knowledge with Neural Networks

Qiyang Chen, A. F. Norcio

Research output: Contribution to journalArticleResearchpeer-review

11 Citations (Scopus)

Abstract

This article presents a neural network approach for user modeling. A set of neural networks is utilized to represent and infer users' task-related characteristics. These networks function as associative memories that can capture the causal relations among users' characteristics for the system adaptation. It is suggested that this approach can be expected to overcome some inherent problems of the conventional stereotyping approaches in terms of pattern recognition and classification of user characteristics.

Original languageEnglish
Pages (from-to)25-40
Number of pages16
JournalPlastics, Rubber and Composites Processing and Applications
Volume9
Issue number1
StatePublished - 1 Dec 1997

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Pattern recognition
Neural networks
Data storage equipment

Cite this

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title = "Modeling a User's Domain Knowledge with Neural Networks",
abstract = "This article presents a neural network approach for user modeling. A set of neural networks is utilized to represent and infer users' task-related characteristics. These networks function as associative memories that can capture the causal relations among users' characteristics for the system adaptation. It is suggested that this approach can be expected to overcome some inherent problems of the conventional stereotyping approaches in terms of pattern recognition and classification of user characteristics.",
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Modeling a User's Domain Knowledge with Neural Networks. / Chen, Qiyang; Norcio, A. F.

In: Plastics, Rubber and Composites Processing and Applications, Vol. 9, No. 1, 01.12.1997, p. 25-40.

Research output: Contribution to journalArticleResearchpeer-review

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AB - This article presents a neural network approach for user modeling. A set of neural networks is utilized to represent and infer users' task-related characteristics. These networks function as associative memories that can capture the causal relations among users' characteristics for the system adaptation. It is suggested that this approach can be expected to overcome some inherent problems of the conventional stereotyping approaches in terms of pattern recognition and classification of user characteristics.

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