000			02143nam a2200181 4500
999			_c32333 _d32333
020			_a978-93-80931-91-3
040			_aBC-EPAU
041			_aeng
100			_a HAN, Jiawei _eComputer scientist
245			_aData mining _bConcepts and techniques
260			_a Waltham, MA _b Morgan Kaufmann/Elsevier _c2012
300			_a703 p. _bIll. _c23 cm.
700			_aKamber, Micheline ; PEI, JIAN
942			_c01 _t0418 _u4.3.3
994			_a04180005
520			_aData Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
653			_aData Mining