Investigations of Neural Networks for Data
Mining Procedures
Sam Eberspacher
November 2, 2007
Abstract
Data mining is a process by which data of different types is evaluated
to determine its value in a given search. The human brain is incredibly
good at this process because it can determine the type of data, process the
language, etc. Neural networks are a computers attempt to simulate what
the brain does by creating artificial neurons which evaluate small pieces
of information. By using a neural network to mine data, the results of the
process will be more accurate than a straight forward procedure. In order
to increase the effectiveness of the network, feedback should be provided
to the network to allow it to ”grow”. The growth of the network would be
done by adding, deleting, or modifying neurons engaged in the network.
1 Introduction
1.1 Purpose
This project is especially useful to search engines or any project that requires
a significant amount of data. The data used by this approach would be more
accurate than a simple algorithm because the network will learn from previous
experiences. This allows the results to become even more accurate as more data
is retrieved and more feedback is given to the network.
1.2 Scope of Study
The development of a neural network will be the most dominant feature of this
project. Data mining is the overall purpose for which the network will be de-
signed, but the initial input processing, and evaluation are the most important
features in this project. Good input processing will be very important, because
the computer can not process language like a human can. This layer of the
network must translate inputs into a format that is understandable by the com-
puter. The next layer, the processing layer, will take the refined inputs and
calculate their overall value, eventually deciding whether the subject is worth
keeping. By having user feedback for several of the results, the computer must
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then be able to refine the neurons to provide a more accurate result. In the event
that in