Neural network data mining uses artificial neural networks to extract data by recognizing patterns in databases. It has numerous practical uses, including analyzing trends in large corporations and extracting patterns from scientific research. It is also used in games, surveillance, and geographic systems.
Neural network data mining is the process of collecting and extracting data by recognizing existing patterns in a database using an artificial neural network. These artificial neural networks are networks that emulate a biological neural network, such as that of the human body. Neural network data mining is mostly used by larger companies or research groups to collect and organize large databases, but it has numerous uses in different fields.
In humans, the neural network is based on neurons. Neurons are the conduits for the nervous system and are responsible for conducting sensory experiences, such as pain and the sense of touch, throughout the body. They communicate through electrical and chemical means and neural networks. The messages they send move rapidly through neural networks and can actually learn to conduct impulses in new ways, especially neurons in the brain.
An artificial neural network is a description of a complex mathematical process that, in some respects, resembles its biological counterpart. The network is made up of artificial neurons, which are also complex mathematical equations, that work by moving information in an input and output process; this process mirrors the functioning of biological neurons.
An artificial neural network (ANN) is a complex structure, but its main purpose is to compute complex processes quickly and efficiently, just like a human neural network. ANNs are also set up so they can learn by performing these processes, making them a form of artificial intelligence. They have a variety of practical uses and can be seen in everything from speech recognition software to radar systems.
ANNs are the key component of neural network data mining. They are able to examine large databases, known as data warehouses, and analyze and extract specific blocks of information through pattern recognition. What that piece of information is depends on the needs of the user. In large companies, they often need to analyze data and notice trends, especially around spending, marketing and sales.
In addition to large corporations, another major user of neural network data mining is the scientific and engineering community. These professionals can use data mining to look at large amounts of information gathered during research and observation and extract whatever patterns they need from that data. This can save many hours of what would otherwise be an exhaustive process.
There are many other areas where neural network data mining is used. For example, it’s used in games, like chess-playing machines, and in surveillance areas, like home security that monitors trends in terrorist activity. More recently, it has been used to mine information about geographic systems, such as statistics vital to climate change.
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