Data Mining: Technologies, Techniques, Tools, and Trends

Rating:
Summary: Fascinating Book
Review: 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.

Rating:
Summary: Excellent for a beginner
Review: As a Novice in data mining I found this book extremely useful. The book describes supporting technologies, data mining techniques and then the directions. Although the book does not go into any technical details such as mathematical reasoning the scope of data mining is clearly explained. I am now really motivated to read the more advanced books in data mining. I would strongly recommend this book for someone who wants to learn about data mining. If you want to learn the algorithms in detail then this is not the book for you.

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Summary: Profound and Thought Provoking Book
Review: As Dr. Dobb's states, this book is quite profound and thought provoking. Not only does it explan all the great things data mining can do for society, it clearly exposes the dangers of data mining. I found this aspect quite fascinating.The chapter on security and privacy aspects of data mining had a great impact on me. Through this book, the author explains the challenging tasks ahead for data mining researchers and developers. They not only have to develop tools that can make associations and correlations, but at the same time protect the privacy of the individuals. The author states that we need the cooperation and collaboration of various technologists, laywers, and policy makers to work togther to make this happen. This is indeed a very moving book, but at the same time the author tries to be quite technical. I would highly recommend this book to anyone working in data management or data mining.

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Summary: Data Mining: Technologies, Techniques, Tools and Trends
Review: Excellent introduction to data mining. Explains complex ideas in a manner that can be clearly undertood

Rating:
Summary: bric-a-brac drivel
Review: I accuse Bhavani Thuraisingham of outright theft in releasing this book. While there are several very rigorous, clear and focused books on data mining on the market (including, "The Elements of Statistical Learning : Data Mining, Inference, and Prediction" by T. Hastie and "Principles of Data Mining" by Heikki Mannila), Ms Thuraisingham's opus isn't even expressed in common English grammar. Excusing misleading (and often incorrect) diagrams, my primary complaint is with the author's jejune and rambling content. When I purchase a book that has the word "techniques" in the title, I expect at least some discussion of concrete methodologies. Instead, the author rambles on about some utopian society where laywers, philosophers and DBAs unite together for the common goal of data extraction. While I understand that this book does not aim to burden its readship with actual numbers or quantifiable terms, it does so at the complete lack of clarity. Data Mining techiques are discussed in such a watered-down fashion that a novice would come away with the idea that Bayesian analysis and linear regression are pretty much similar techniques. My confusion with data mining often seemed proportional to the page number that I was on. There are many books on the market discussing this popular topic; this is one of the worst.

Rating:
Summary: bric-a-brac drivel
Review: I accuse Bhavani Thuraisingham of outright theft in releasing this book. While there are several very rigorous, clear and focused books on data mining on the market (including, "The Elements of Statistical Learning : Data Mining, Inference, and Prediction" by T. Hastie and "Principles of Data Mining" by Heikki Mannila), Ms Thuraisingham's opus isn't even expressed in common English grammar. Excusing misleading (and often incorrect) diagrams, my primary complaint is with the author's jejune and rambling content. When I purchase a book that has the word "techniques" in the title, I expect at least some discussion of concrete methodologies. Instead, the author rambles on about some utopian society where laywers, philosophers and DBAs unite together for the common goal of data extraction. While I understand that this book does not aim to burden its readship with actual numbers or quantifiable terms, it does so at the complete lack of clarity. Data Mining techiques are discussed in such a watered-down fashion that a novice would come away with the idea that Bayesian analysis and linear regression are pretty much similar techniques. My confusion with data mining often seemed proportional to the page number that I was on. There are many books on the market discussing this popular topic; this is one of the worst.

Rating:
Summary: Terrible book
Review: I found this book absolutely awful, lacking coherence and filled with unclear, often ambiguous, examples. I have discovered that my last review was taken down and replaced with 2 five-star glowing reviews, all from users who seem to exclusively rate (and very highly at that) this particular author's books... My advice to people considering purchasing this book is to page through it at your local bookstore. At [this price], one expects textbook quality material; not a shabby, tossed together ramble.

Rating:
Summary: Great book for a non computer scientist
Review: 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.

Rating:
Summary: One of the best in data mining
Review: 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

Rating:
Summary: Enlightening and Enjoyable Reading
Review: 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.