CH07_withFigures - Chapter 7 DATA, TEXT, AND WEB MINING...

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Chapter 7 DATA, TEXT, AND WEB MINING
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Learning Objectives Define data mining and list its objectives and benefits Understand different purposes and applications of data mining Understand different methods of data mining, especially clustering and decision tree models Build expertise in use of some data mining software
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Learning Objectives Learn the process of data mining projects Understand data mining pitfalls and myths Define text mining and its objectives and benefits Appreciate use of text mining in business applications Define Web mining and its objectives and benefits
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Data Mining Concepts and Applications Six factors behind the sudden rise in popularity of data mining 1. General recognition of the untapped value in large databases; 2. Consolidation of database records tending toward a single customer view; 3. Consolidation of databases, including the concept of an information warehouse; 4. Reduction in the cost of data storage and processing, providing for the ability to collect and accumulate data; 5. Intense competition for a customer’s attention in an increasingly saturated marketplace; and 6. The movement toward the de-massification of business practices
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Data Mining Concepts and Applications Data mining (DM) A process that uses statistical, mathematical, artificial intelligence and machine-learning techniques to extract and identify useful information and subsequent knowledge from large databases
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Data Mining Concepts and Applications Major characteristics and objectives of data mining Data are often buried deep within very large databases, which sometimes contain data from several years; sometimes the data are cleansed and consolidated in a data warehouse The data mining environment is usually client/server architecture or a Web-based architecture
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Data Mining Concepts and Applications Major characteristics and objectives of data mining Sophisticated new tools help to remove the information ore buried in corporate files or archival public records; finding it involves massaging and synchronizing the data to get the right results. The miner is often an end user, empowered by data drills and other power query tools to ask ad hoc questions and obtain answers quickly, with little or no programming skill
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Data Mining Concepts and Applications Major characteristics and objectives of data mining Striking it rich often involves finding an unexpected result and requires end users to think creatively Data mining tools are readily combined with spreadsheets and other software development tools; the mined data can be analyzed and processed quickly and easily Parallel processing is sometimes used because of the large amounts of data and massive search efforts
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This note was uploaded on 03/31/2010 for the course IS 425 taught by Professor Lemon during the Spring '10 term at University of Maryland Baltimore.

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CH07_withFigures - Chapter 7 DATA, TEXT, AND WEB MINING...

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