Read "Data Mining Technology (third edition)"-Apply to marketing, sales and customer relationship management--data mining

Source: Internet
Author: User

Read "Data Mining Technology (third edition)"-Thoughts on marketing, sales and customer relationship management

This book is not a purely data mining theory book, you can probably guess from the subtitle of this book. For a layman like me in the field of data mining, there is not much difficulty in reading this book. This book is not a pure technology book, but its understanding of technical theory is very helpful. The author introduces the concepts and techniques of data mining, and then guides readers into the world of data mining.

The examples in the book are data mining cases that the author encounters over decades of work, encounters problems and summaries of solutions, rather than fabricated cases, from which the author's accomplishments in the field of data mining can be seen.

The author of the data mining algorithms and principles, although introduced, but not many, so for the first into the field of data mining people read this book or no difficulties, for data mining professionals, if you want to know the specific algorithm or read a special book it. For data mining software operations, this book is not covered.

This book focuses on the interpretation of technology and the practical application of data mining. For a variety of topics, the authors are introduced. Even for complex topics, the authors make a concise presentation, and unlike other data mining bibliographies, the authors minimize the use of technical terms and mathematical formulas. Each chapter is a reminder of the author's valuable experience.

The contents of this book are divided into four parts. The first part discusses the business context of data mining. The author in order to explain the method of DM, but also bedding some basic knowledge of statistics and allusions. The second part introduces the guidance data mining technology, including decision tree, artificial neural network, nearest neighbor method: Based on storage reasoning and collaborative filtering, shopping basket analysis and association rules. The third part introduces the data mining technology without guiding learning, such as cluster analysis. In the last part, the data in the data mining terminology is introduced, and the current large data and so on are the hot concepts.

How telecom operators can find leaders in a group by calling data. Who is using the fax machine at home? How Google became the ruler of the world. What information does your friend reveal about you on Facebook? Want to know the answers to these questions? In the 16th chapter of the Book, Link analysis (linkanalysis) will tell you the answer to the question. In addition to these, a lot of fascinating questions you can find in this book. Here is not a list.

Read this book to find a problem. Perhaps due to the limitations of paper space, the end of the book without references and glossary index, for query terminology and so on a little inconvenience.

In short, as the author of this book says, this book is such a book that you may want to read it when you start your own data mining career.

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