Data Mining: Multimedia, Soft Computing, and Bioinformatics
暫譯: 資料探勘：多媒體、軟體計算與生物資訊學

Sushmita Mitra, Tinku Acharya

Data Mining: Multimedia, Soft Computing, and Bioinformatics
  • 出版商: Wiley
  • 出版日期: 2003-09-25
  • 售價: $1,080
  • 貴賓價: 9.8 折 $1,058
  • 語言: 英文
  • 頁數: 424
  • 裝訂: Hardcover
  • ISBN: 0471460540
  • ISBN-13: 9780471460541
  • 相關分類: Data-mining

    • 下單後立即進貨 (約5~7天)

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商品描述

 

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

傳統硬體與新興軟體計算方法在多媒體數據挖掘中的入門指南

隨著數位革命使得大量高維度的多媒體數據變得可用，這也挑戰了用戶從過去無法想像的龐大數據集中提取所需信息的能力。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——如模糊集合、人工神經網絡、遺傳算法和粗糙集合——則提供了應用各種數據類型於多種重要功能的機會，通過以低成本的解決方案處理現實生活中的不確定性。《數據挖掘：多媒體、軟體計算與生物資訊學》提供了對基本和進階數據挖掘技術的易讀介紹。

這本可讀性強的調查描述了針對各種數據類型的數據挖掘策略，包括數值和字母數字格式、文本、圖像、視頻、圖形及其混合表示。除了傳統的數據挖掘概念和功能——如分類、聚類和規則挖掘——作者還強調了多媒體應用和生物資訊學中的當前議題。全書討論的主要主題包括：
- 軟體計算在數據挖掘中的角色及其原則
- 字串匹配的原則和經典算法及其在數據（主要是文本）挖掘中的角色
- 無損和有損技術的數據壓縮原則，包括它們在數據挖掘中的範疇
- 使用匹配追求在原始和壓縮數據領域中訪問數據
- 在挖掘生物數據庫中的應用

目錄

前言
1. 數據挖掘介紹
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. 使用軟體計算的規則挖掘
9. 多媒體數據挖掘
10. 生物資訊學：一個應用
索引
關於作者

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