滿額折
Data Mining: Multimedia, Soft Computing And Bioinformatics
商品資訊
ISBN13：9780471460541
出版社：John Wiley & Sons Inc
作者：Mitra
出版日：2003/09/11
裝訂／頁數：平裝／424頁
定價
：NT$ 7180 元優惠價
：
90 折 6462 元
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商品簡介
作者簡介
目次
商品簡介
* First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches
* Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining
* Discusses principles and classical algorithms on string matching and their role in data mining
* Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining
* Discusses principles and classical algorithms on string matching and their role in data mining
作者簡介
SUSHMITA MITRA, PHD, is a Professor at Machine Intelligence Unit, Indian Statistical Institute, in Calcutta. She is a coauthor of Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing, also published by Wiley.
TINKU ACHARYA, PHD, Senior Executive vice president and Chief Science Officer of Avisere Inc., Tucson, Arizona, is involved in multimedia data mining applications. He is also an adjunct professor in the Department of Electrical Engineering at Arizona State University. He was recognized as the Most Prolific Inventor of Intel Corporation Worldwide in 1999.
TINKU ACHARYA, PHD, Senior Executive vice president and Chief Science Officer of Avisere Inc., Tucson, Arizona, is involved in multimedia data mining applications. He is also an adjunct professor in the Department of Electrical Engineering at Arizona State University. He was recognized as the Most Prolific Inventor of Intel Corporation Worldwide in 1999.
目次
Preface.
1. Introduction to Data Mining.
2. Soft Computing.
3. Multimedia Data Compression.
4. String Matching.
5. Classification in Data Mining.
6. Clustering in Data Mining.
7. Association Rules.
8. Rule Mining with Soft Computing.
9. Multimedia Data Mining.
10. Bioinformatics: An Application.
Index.
About the Authors.
1. Introduction to Data Mining.
2. Soft Computing.
3. Multimedia Data Compression.
4. String Matching.
5. Classification in Data Mining.
6. Clustering in Data Mining.
7. Association Rules.
8. Rule Mining with Soft Computing.
9. Multimedia Data Mining.
10. Bioinformatics: An Application.
Index.
About the Authors.
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