|
||||||||||||||||||||
|
||||||||||||||||||||
|
||||||||||||||||||||
よく一緒に購入されている商品
商品の説明
内容説明
The increasing volume of data in modern business and science calls for more complex and sophisticated tools. Although advances in data mining technology have made extensive data collection much easier, it's still always evolving and there is a constant need for new techniques and tools that can help us transform this data into useful information and knowledge.
Since the previous edition's publication, great advances have been made in the field of data mining. Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream, mining social networks, and mining spatial, multimedia and other complex data. Each chapter is a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. This is the resource you need if you want to apply today's most powerful data mining techniques to meet real business challenges.
* 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
著者について
Jiawei Han is Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. Well known for his research in the areas of data mining and database systems, he has received many awards for his contributions in the field, including the 2004 ACM SIGKDD Innovations Award. He has served as Editor-in-Chief of ACM Transactions on Knowledge Discovery from Data, and on editorial boards of several journals, including IEEE Transactions on Knowledge and Data Engineering and Data Mining and Knowledge Discovery.
Micheline Kamber is a researcher with a passion for writing in easy-to-understand terms. She has a master's degree in computer science (specializing in artificial intelligence) from Concordia University, Canada.
Jian Pei is Associate Professor of Computing Science and the director of Collaborative Research and Industry Relations at the School of Computing Science at Simon Fraser University, Canada. In 2002-2004, he was an Assistant Professor of Computer Science and Engineering at the State University of New York (SUNY) at Buffalo. He received a Ph.D. degree in Computing Science from Simon Fraser University in 2002, under Dr. Jiawei Han's supervision.
登録情報
|
類似した商品から提示されたタグ(詳細)関連タグ(この商品に近い関連キーワード)を追加する++最初のタグになります
|
カスタマーレビュー
Amazon.com で最も参考になったカスタマーレビュー (beta)
Amazon.com:
10件のカスタマーレビュー
5 人中、5人の方が、｢このレビューが参考になった｣と投票しています。
Comprehensive Overview
2011/8/9
形式:ハードカバー|Amazon Vine™ レビュー
(詳しくはこちら)
Data Mining is a comprehensive overview of the field, and I think it is best for a graduate class in data mining, or perhaps as a reference book. The book's focus is on technique (i.e., how to analyze data, including preparation), and it addresses all the major topics in the field including data storage and pre-processing. However, the book is really about classification methods, and the 2 chapters on cluster analysis are particularly strong and thorough.
For those looking for specific examples, applications, and domain knowledge, I would recommend Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management by Linoff & Berry. However, for analytic techniques, this reference book is far superior.
For those looking for specific examples, applications, and domain knowledge, I would recommend Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management by Linoff & Berry. However, for analytic techniques, this reference book is far superior.
10 人中、8人の方が、｢このレビューが参考になった｣と投票しています。
Oriented for Academia
2011/10/17
形式:ハードカバー|Amazon Vine™ レビュー
(詳しくはこちら)
This was written to be a textbook from the start, complete with question-sets from at the end of every chapter. If you're a student you won't have any choice as to the book selection, however if you are looking at this more from a practical commercial standpoint you will have many choices and this may not be the best one. I think in many ways it tries to be very encyclopedic and covers a huge amount of background information that is probably perfunctory in industry. The book would be more useful as a desk reference with heavy editing, more real-life examples... perhaps along the lines of case studies that may fit outside of a curriculum based arc.
Minuses:
- Not very illustrative, when there are diagrams and visual examples they tend to be very bare bones
- Some of the screen shots are absolutely terrible resolution (ex. page 602/603)
Minuses:
- Not very illustrative, when there are diagrams and visual examples they tend to be very bare bones
- Some of the screen shots are absolutely terrible resolution (ex. page 602/603)
3 人中、3人の方が、｢このレビューが参考になった｣と投票しています。
A Detailed Data Mining book!
2011/8/19
形式:ハードカバー|Amazon Vine™ レビュー
(詳しくはこちら)
Data Mining: Concepts and Techniques book is detailed, well-organized with good introduction. Every chapter has sub-headings and it is in a nice order explained with figures. There is introduction in the beginning of the chapter but it would be sufficient if you already read a data mining book. If you want to read more introduction it is better to go through few more books. There are small examples and exercises throughout the book. There is exclusively a chapter dedicated for outlier detection. This is better than few other data mining books that I had referred for the reason it covers a wide range of topics. There is detailed introduction about each chapter of the book. The contents of this book is available in pdf format and also there are slide presentations for each chapter. It is definitely worth reading this book.
これらのレビューは参考になりましたか？
ご意見はクチコミでお聞かせください。
リストマニア
関連商品を探す
同じキーワードの商品を探す
フィードバック
- カタログ情報、または画像について報告
- 著者からのコメント
- 出版社からのコメント
|
