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SEARCH AND CLASSIFICATION OF "INTERESTING" BUSINESS APPLICATIONS IN THE WORLD WIDE WEB USING A NEURAL NETWORK APPROACH
Karl
Kurbel, Kirti Singh, Frank Teuteberg
Europe University Viadrina Frankfurt (Oder), Germany
Abstract:
A database of business Internet applications developed
at Europe University Viadrina is in the process of being filled
with "interesting" WWW applications. As the number of
WWW sites is huge and still growing fast, the question is how to
find the right applications for the database. In this paper, a
neural network approach is proposed to automate the process of
searching and selecting candidate applications. 23 configurations
of neural networks have been tested: 15 versions of the
multi-layer perceptron, four generalized feed-forward networks
and four modular networks. Results from training and testing
those networks are presented and discussed.
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