Data Mining: Multimedia, Soft Computing, and Bioinformatics

Sushmita Mitra, Tinku Acharya

Data Mining: Multimedia, Soft Computing, and Bioinformatics
  • 出版商: Wiley
  • 出版日期: 2003-09-25
  • 售價: $1,026
  • 語言: 英文
  • 頁數: 424
  • 裝訂: Hardcover
  • ISBN: 0471460540
  • ISBN-13: 9780471460541
  • 相關分類: 生物資訊 Bioinformatics、Data-mining

    • 下單後立即進貨 (約5~7天)

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Summary

A primer on traditional hard and emerging soft computing approaches for mining multimedia data

While the digital revolution has made huge volumes of high dimensional multimedia data available, it has also challenged users to extract the information they seek from heretofore unthinkably huge datasets. Traditional hard computing data mining techniques have concentrated on flat-file applications. Soft computing tools–such as fuzzy sets, artificial neural networks, genetic algorithms, and rough sets–however, offer the opportunity to apply a wide range of data types to a variety of vital functions by handling real-life uncertainty with low-cost solutions. Data Mining: Multimedia, Soft Computing, and Bioinformatics provides an accessible introduction to fundamental and advanced data mining technologies.

This readable survey describes data mining strategies for a slew of data types, including numeric and alpha-numeric formats, text, images, video, graphics, and the mixed representations therein. Along with traditional concepts and functions of data mining–like classification, clustering, and rule mining–the authors highlight topical issues in multimedia applications and bioinformatics. Principal topics discussed throughout the text include:

  • The role of soft computing and its principles in data mining
  • Principles and classical algorithms on string matching and their role in data (mainly text) mining
  • Data compression principles for both lossless and lossy techniques, including their scope in data mining
  • Access of data using matching pursuits both in raw and compressed data domains
  • Application in mining biological databases

Table of Contents

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.

商品描述(中文翻譯)

 


摘要



關於傳統硬體和新興軟體計算方法在挖掘多媒體數據方面的入門指南


數字革命使得大量高維多媒體數據變得可用，同時也挑戰用戶從以前無法想像的大數據集中提取所需的信息。傳統的硬體計算數據挖掘技術主要集中在平面文件應用上。然而，軟體計算工具（如模糊集、人工神經網絡、遺傳算法和粗糙集）提供了應用各種數據類型到各種重要功能的機會，通過低成本解決方案處理現實生活中的不確定性。《數據挖掘：多媒體、軟體計算和生物信息學》提供了對基礎和高級數據挖掘技術的易於理解的介紹。


這本易讀的調查書描述了各種數據類型的數據挖掘策略，包括數字和字母數據格式、文本、圖像、視頻、圖形以及其中的混合表示。除了傳統的數據挖掘概念和功能（如分類、聚類和規則挖掘）外，作者還強調了多媒體應用和生物信息學中的熱門問題。全書討論的主要主題包括：



  • 軟體計算及其在數據挖掘中的原則

  • 字串匹配的原則和經典算法及其在數據（主要是文本）挖掘中的作用

  • 無損和有損數據壓縮技術的原則，包括它們在數據挖掘中的應用範圍

  • 在原始和壓縮數據領域中使用匹配追蹤的數據訪問

  • 在生物數據庫中的挖掘應用



目錄



前言


1. 數據挖掘簡介


2. 軟體計算


3. 多媒體數據壓縮


4. 字串匹配


5. 數據挖掘中的分類


6. 數據挖掘中的聚類


7. 關聯規則


8. 軟體計算中的規則挖掘


9. 多媒體數據挖掘


10. 生物信息學：一個應用


索引


關於作者


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