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Papers > Technology > Data Mining
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1. datamining
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Data Mining |
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What is Data mining? Databases today can range in size into the terabytes — more than 1,000,000,000,000 bytes of data.Within these masses of data lies hidden information of strategic importance. ... The newest answer is data mining, which is being used both to increase revenues and to reduce costs. ... Innovative organizations worldwide are already using data mining to locate and appeal to higher-value customers, to reconfigure their product offerings to increase sales, and to minimize losses due to error or fraud. Data mining is a process that uses a variety of data analysis tools to discover patterns and relationships in data that may be used to make valid predictions. Generally speaking, knowledge discovery or data mining in databases is a nontrivial extraction of previously unknown and potentially useful information from data. Data mining is essentially the computer-assisted process of information analysis. The data mining process seeks to build a better understanding and characterization of data useful for further analysis. Data Mining techniques unifies existing methods from machine learning, pattern recognition, databases, statistics, data visualization, etc. The term data mining refers loosely to the process of semi automatically analyzing large databases to find useful patterns. Like knowledge discovery in artificial intelligence, or statistical analysis, data mining attempts to discover rules and patterns from data. However data mining differs form machine learning and statistics in that it deals with large volumes of data, stored primarily on disk. That is, data mining deals with “knowledge discovery in databases”. Extraction of interesting (non-trivial, implicit, previously unknown and potentially useful) information or patterns from data in large databases is data mining. Alternative names and their “inside stories”: Data mining: a misnomer? Knowledge discovery(mining) in databases (KDD), knowledge extraction, data/pattern analysis, data archeology, data dredging, information harvesting, business intelligence, etc. |
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Title: Data Mining
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