Mining the Web: Discovering Knowledge for Hypertext Data
暫譯: 網路挖掘:為超文本數據發現知識
Soumen Chakrabarti
- 出版商: Morgan Kaufmann
- 出版日期: 2002-10-09
- 定價: $1,980
- 售價: 5.0 折 $990
- 語言: 英文
- 頁數: 344
- 裝訂: Hardcover
- ISBN: 1558607544
- ISBN-13: 9781558607545
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相關分類:
大數據 Big-data、Machine Learning、Web-crawler 網路爬蟲
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相關主題
商品描述
Mining the Web: Discovering Knowledge from Hypertext Data is the first book devoted entirely to techniques for producing knowledge from the vast body of unstructured Web data. Building on an initial survey of infrastructural issues--including Web crawling and indexing--Chakrabarti examines low-level machine learning techniques as they relate specifically to the challenges of Web mining. He then devotes the final part of the book to applications that unite infrastructure and analysis to bring machine learning to bear on systematically acquired and stored data. Here the focus is on results: the strengths and weaknesses of these applications, along with their potential as foundations for further progress. From Chakrabarti's work--painstaking, critical, and forward-looking--readers will gain the theoretical and practical understanding they need to contribute to the Web mining effort.
Preface. Introduction. I Infrastructure: Crawling the Web. Web search. II Learning: Similarity and clustering. Supervised learning for text. Semi-supervised learning. III Applications: Social network analysis. Resource discovery. The future of Web mining.
商品描述(中文翻譯)
挖掘網路:從超文本數據中發現知識是第一本專門探討從龐大的非結構化網路數據中產生知識的技術的書籍。該書基於對基礎設施問題的初步調查,包括網路爬蟲和索引,查克拉巴提(Chakrabarti)檢視了與網路挖掘挑戰相關的低階機器學習技術。接著,他將書的最後部分專注於將基礎設施和分析結合起來的應用,將機器學習應用於系統性獲取和儲存的數據。在這裡,重點在於結果:這些應用的優缺點,以及它們作為進一步發展基礎的潛力。透過查克拉巴提的工作——細心、批判且具前瞻性——讀者將獲得他們在網路挖掘工作中所需的理論和實踐理解。
目錄
前言。介紹。I 基礎設施:爬取網路。網路搜尋。II 學習:相似性和聚類。文本的監督學習。半監督學習。III 應用:社交網路分析。資源發現。網路挖掘的未來。