Contemporary Perspectives in Data Mining, Volume 2

Business & Finance, Economics, Statistics, Finance & Investing, Finance, Nonfiction, Science & Nature, Mathematics
Cover of the book Contemporary Perspectives in Data Mining, Volume 2 by , Information Age Publishing
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Author: ISBN: 9781681230894
Publisher: Information Age Publishing Publication: July 1, 2015
Imprint: Information Age Publishing Language: English
Author:
ISBN: 9781681230894
Publisher: Information Age Publishing
Publication: July 1, 2015
Imprint: Information Age Publishing
Language: English

The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are in marketing (customer loyalty, identifying profitable customers, instore promotions, ecommerce populations); in business (teaching data mining, efficiency of the Chinese automobile industry, moderate asset allocation funds); and techniques (veterinary predictive models, data integrity in the cloud, irregular pattern detection in a mobility network and road safety modeling.)

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The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are in marketing (customer loyalty, identifying profitable customers, instore promotions, ecommerce populations); in business (teaching data mining, efficiency of the Chinese automobile industry, moderate asset allocation funds); and techniques (veterinary predictive models, data integrity in the cloud, irregular pattern detection in a mobility network and road safety modeling.)

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