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商品描述
A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today’s often unmanageable volumes of data by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures. Service-Oriented Distributed Knowledge Discovery presents techniques, algorithms, and systems based on the service-oriented paradigm. Through detailed descriptions of real software systems, it shows how the techniques, models, and architectures can be implemented.
The book covers key areas in data mining and service-oriented computing. It presents the concepts and principles of distributed knowledge discovery and service-oriented data mining. The authors illustrate how to design services for data analytics, describe real systems for implementing distributed knowledge discovery applications, and explore mobile data mining models. They also discuss the future role of service-oriented knowledge discovery in ubiquitous discovery processes and large-scale data analytics.
Highlighting the latest achievements in the field, the book gives many examples of the state of the art in service-oriented knowledge discovery. Both novices and more seasoned researchers will learn useful concepts related to distributed data mining and service-oriented data analysis. Developers will also gain insight on how to successfully use service-oriented knowledge discovery in databases (KDD) frameworks.
商品描述(中文翻譯)
一種新的分散式大規模資料挖掘方法，服務導向的知識發現透過利用資料挖掘和機器學習的分散模型及技術，從當今常常無法管理的大量資料中提取有用的知識。《服務導向的分散知識發現》介紹了基於服務導向範式的技術、演算法和系統。通過對真實軟體系統的詳細描述，展示了這些技術、模型和架構如何實現。
本書涵蓋了資料挖掘和服務導向計算的關鍵領域。它介紹了分散知識發現和服務導向資料挖掘的概念和原則。作者說明了如何設計資料分析服務，描述了實現分散知識發現應用的真實系統，並探討了移動資料挖掘模型。他們還討論了服務導向知識發現在無所不在的發現過程和大規模資料分析中的未來角色。
本書突顯了該領域的最新成就，提供了許多服務導向知識發現的最先進範例。無論是新手還是更有經驗的研究人員，都能學到與分散資料挖掘和服務導向資料分析相關的有用概念。開發人員也將獲得如何在資料庫（KDD）框架中成功使用服務導向知識發現的見解。
