Customer Reviews

Data Mining: Technologies, Techniques, Tools, and Trends

5 star:		(14)
4 star:		(1)
3 star:		(0)
2 star:		(0)
1 star:		(2)

 

 

This is the second in a series of books by the author on data management and data mining for technical managers. While the book is written at a high level and aimed at managers, it gives a very interesting overview of data mining. The author has thought about some deep issues such as privacy back in 1998 when we are beginning to see debates emerge only within the past year. Author is a visionary and has very good insights.

This book, while it may be outdated as its over 4 yrs old and so much has happened in data mining, is very easy to read and ideas well explained. I am not a computer scientist and found this book very interesting. I will recommend it to a beginner who wants to get a very broad overview of data mining.

If any one ask me where can I can start, I will not hesitate to recommend this book.

If you ride with the author, you will find yourself effortlessly skim through all the important topics on data mining. In Part I, she tells you what the technologies are involved, In part II, she zooms through nearly all the important techniques and tools; however, it is not an encyclopedia type coverage. It gives you a good feel about the subject.

Finally in Part III, she presents the future trends, again she covers it all (somewhat over saying it). In summary, this book is a concise introduction, and overview of data mining area. It is an excellent book for novice, administrators, managers, in fact anyone who want to understand without the technical details.

I thoroughly enjoyed reading this book. It is very well written and easy to understand. Dr. Thuraisingham separates the book into three parts. Part 1 gives an overview of data mining technologies. The relationships between data management, data mining and data warehousing are clearly explained. Part 2 starts with an excellent overview of the process of data mining with many real-world examples. My only issue with this book is about chapter 7. While the author tries to explain many data mining techniques, perhaps she could have used a case study or a scenario to illustrate these techniques. Part 3 is the best part of this book. Dr. Thuraisingham explains mining distributed data as well as multimedia data. These are some of the current trends and I look forward to learning more about these topics in the future. I found the two chapters on web mining and security very enlightening. The author describes the advantages of data mining as well as discusses the potential problems with it. This balanced view point is rare to find in many of my other readings on data mining as of yet. I must say that while this book is clearly not for an expert in data mining, it is certainly one of the best in the field for a novice. It is indeed remarkable that someone as eminent as Dr. Thuraisingham, with several prominent research papers to her credit in secure data management, to have produced such an easy-to-understand book in data mining.

As a lawyer I found this book fascinating. I have been a child's advocate since my postgraduate studies at the University of Cambridge over a decade ago, and have read of Dr. Thuraisingham's work on applying data mining for protecting children from inappropriate content on the Internet. This work got me very interested in the subject and I wanted to know more about data mining. Dr. Thuraisingham's book provided me with an excellent introduction to the field. I was especially interested in the chapter on security and privacy aspects of data mining. The potential consequences are very intriguing. It will be interesting to see the policies and procedures that could result from data mining, security and privacy. I thoroughly enjoyed reading all of the chapters on data mining trends. For example, the chapter on distributed data mining showed that people living in different countries could collaboratively carry out mining and extract patterns. There could be interesting legal implications. The chapter on multimedia data mining offered insights into mining newspaper articles, law reviews and pictures. The chapter on mining the web enlightened me on the potential goldmine that is out there on the Internet. It appears that while data mining tools may be essential for finding patterns, we simply cannot forget about security and privacy. I am now very motivated to read more about this topic and learn all the latest developments related to data mining and privacy.

This book, besides enumerating with very little detail the already well-known data mining techniques, does not say anything about the mathematics behind all the techniques mentioned. Although it might be well written and mention a wide range of data mining techniques, it is useless as the most books in this area, in particular for people actively involved in the field.

I have read quite a few books in data mining and some of them are quite difficult to understand. This is the first book that helped me to understand what this area is all about. It does not go into depth, but it certainly explains the complex ideas in simple terms. I found the chapter on privacy extremely interesting. I would recommend it to anyone who wants to learn about data mining

For someone with very little knowledge of computing, I found this book very useful. I am now eager to read more books in the field.

This book, while it may be outdated as its over 4 yrs old and so much has happened in data mining, is very easy to read and ideas well explained. I am not a computer scientist and found this book very interesting. I will recommend it to a beginner who wants to get a very broad overview of data mining.

I have an accounting background specializing in tax and policy issues with some knowledge of IT. I have heard a lot about data mining, and based on the reviews that I have read on data mining, I decided to read Dr. Thuraisingham's book. I found it extremely interesting and useful. It gave me just enough information of a broad set of topics in data mining and knowledge discovery including the technologies for data mining and the trends in data mining. I found the examples listed quite interesting. I would now like to learn more about applying data mining for accounting and taxation.