Concept Data Analysis : Theory and Applications
暫譯: 概念數據分析：理論與應用

Claudio Carpineto, Giovanni Romano

Concept Data Analysis : Theory and Applications
  • 出版商: Wiley
  • 出版日期: 2004-09-03
  • 定價: $4,200
  • 售價: 9.5 折 $3,990
  • 語言: 英文
  • 頁數: 220
  • 裝訂: Hardcover
  • ISBN: 0470850558
  • ISBN-13: 9780470850558
  • 相關分類: Data Science

    • 立即出貨 (庫存 < 3)

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商品描述

Description:

The advent of the Web, along with the unprecedented amount of data available in electronic format, has dramatically increased the need for tools that support the users in retrieving, understanding and mining the information and knowledge contained in such data.

Concept data analysis differs from statistical data analysis in that the emphasis is on recognising and generalising the structure of symbolic data through a mathematical representation termed a concept lattice. Thanks to its simplicity, elegance and versatility, concept data analysis can effectively support various kinds of content management tasks using different or heterogeneous types of data.

  • Provides a comprehensive treatment of the full range of techniques developed for concept data analysis covering creation, maintenance, display and manipulation of concept lattices
  • Presents application areas such as information retrieval and mining from text and web data as well as rule mining from structured data
  • Features two detailed case studies; exploring the content of the ACM Digital Library using an interface that integrates multiple search functionalities; and mining web retrieval results through the system CREDO, a version of which is available on-line for testing

Concept Data Analysis: Theory & Applications is essential for researchers active in information processing and data mining as well as industry practitioners who are interested in creating a commercial product for concept data analysis or developing content management applications. Computer science students will also find it invaluable.

 

Table of Contents:

Foreword.

Preface.

I Theory and algorithms.

1 Theoretical foundations.

1.1 Basic notions of orders and lattices.

1.2 Context, concept, and concept lattice.

1.3 Many-valued contexts.

1.4 Bibliographic notes.

2 Algorithms.

2.1 Constructing concept lattices.

2.2 Incremental lattice update.

2.3 Visualization.

2.4 Adding knowledge to concept lattices.

2.5 Bibliographic notes.

II Applications.

3 Information retrieval.

3.1 Query modi.cation.

3.2 Document ranking

4 Text mining.

4.1 Mining the content of the ACM Digital Library.

4.2 MiningWeb retrieval results with CREDO.

4.3 Bibliographic notes.

5 Rule mining.

5.1 Implications.

5.2 Functional dependencies.

5.3 Association rules.

5.4 Classification rules.

5.5 Bibliographic notes.

商品描述(中文翻譯)

**描述：**
網路的出現以及電子格式中前所未有的數據量，顯著增加了支持用戶檢索、理解和挖掘這些數據中所包含的信息和知識的工具需求。
概念數據分析與統計數據分析的不同之處在於，前者強調通過一種稱為概念格的數學表示來識別和概括符號數據的結構。由於其簡單性、優雅性和多功能性，概念數據分析能有效支持各種內容管理任務，使用不同或異質類型的數據。
- 提供對概念數據分析所開發的全範圍技術的全面處理，包括概念格的創建、維護、顯示和操作
- 提出應用領域，如信息檢索和從文本及網頁數據中挖掘，以及從結構化數據中挖掘規則
- 特色兩個詳細的案例研究；探索使用整合多種搜索功能的介面來訪問ACM數字圖書館的內容；以及通過系統CREDO挖掘網頁檢索結果，其中一個版本可在線測試

*《概念數據分析：理論與應用》* 對於活躍於信息處理和數據挖掘的研究人員以及對創建概念數據分析商業產品或開發內容管理應用程序感興趣的行業從業者來說是必不可少的。計算機科學學生也會發現它非常有價值。

**目錄：**
前言。
序言。
I 理論與算法。
1 理論基礎。
1.1 順序和格的基本概念。
1.2 上下文、概念和概念格。
1.3 多值上下文。
1.4 參考文獻。
2 算法。
2.1 構建概念格。
2.2 增量格更新。
2.3 可視化。
2.4 向概念格添加知識。
2.5 參考文獻。
II 應用。
3 信息檢索。
3.1 查詢修改。
3.2 文檔排名。
4 文本挖掘。
4.1 挖掘ACM數字圖書館的內容。
4.2 使用CREDO挖掘網頁檢索結果。
4.3 參考文獻。
5 規則挖掘。
5.1 含義。
5.2 功能依賴。
5.3 關聯規則。
5.4 分類規則。
5.5 參考文獻。

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