Internet Data Mining

Internet Data Mining

Kuldeep Kumar (Bond University, Australia) and John Baker (Universal College of Learning, New Zealand)
Copyright: © 2002 |Pages: 18
DOI: 10.4018/978-1-930708-21-1.ch015
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Abstract

Data mining has emerged as one of the hottest topics in recent years. It is an extraordinarily broad area and is growing in several directions. With the advancement of the Internet and cheap availability of powerful computers, data is flooding the market at a tremendous pace. However, the technology for navigating, exploring, visualizing and summarizing large databases are still in their infancy. The quantity and diversity of data available to make decisions has increased dramatically during the past decade. Large databases are being built to hold and deliver these data. Data mining is defined as the process of seeking interesting or valuable information within large data sets. Some examples of data mining applications in the area of management science are analysis of direct-mailing strategies, sales data analysis for customer segmentation, credit card fraud detection, mass customization, etc. With the advancement of the Internet and World Wide Web, both management scientists and interested end-users can get large data sets for their research from this source. The Web not only contains a vast amount of useful information, but also provides a powerful infrastructure for communication and information sharing. For example, Ma, Liu and Wong (2000) have developed a system called DS-Web that uses the Web to help data mining. A recent survey on Web mining research can be seen in the paper by Kosala and Blockeel (2000).

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