Learning from Data Streams in Evolving Environments: Methods and Applications (Studies in Big Data)
暫譯: 在演變環境中從數據流中學習:方法與應用(大數據研究)
- 出版商: Springer
- 出版日期: 2018-08-09
- 售價: $4,510
- 貴賓價: 9.5 折 $4,285
- 語言: 英文
- 頁數: 317
- 裝訂: Hardcover
- ISBN: 3319898027
- ISBN-13: 9783319898025
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相關分類:
大數據 Big-data
海外代購書籍(需單獨結帳)
相關主題
商品描述
This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field.
- Provides multiple examples to facilitate the understanding data streams in non-stationary environments;
- Presents several application cases to show how the methods solve different real world problems;
- Discusses the links between methods to help stimulate new research and application directions.
商品描述(中文翻譯)
這本編輯書籍涵蓋了針對由不斷演變的非穩態過程生成的數據流學習問題的最新技術、方法和工具的進展。其目標是討論和概述專門用於管理、利用和解釋非穩態環境中數據流的先進技術、方法和工具。本書包括理解非穩態環境中數據流學習問題所需的概念、定義和背景,並綜合了該領域的最新技術,討論了先進的方面和概念,並提出了該領域的開放問題和未來挑戰。
- 提供多個範例以促進對非穩態環境中數據流的理解;
- 提出幾個應用案例以展示這些方法如何解決不同的現實世界問題;
- 討論方法之間的聯繫,以幫助激發新的研究和應用方向。