Data Visualization and Knowledge Engineering: Spotting Data Points with Artificial Intelligence
暫譯: 數據視覺化與知識工程:利用人工智慧識別數據點
Hemanth, Jude, Bhatia, Madhulika, Geman, Oana
- 出版商: Springer
- 出版日期: 2019-08-10
- 售價: $4,510
- 貴賓價: 9.5 折 $4,285
- 語言: 英文
- 頁數: 319
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3030257967
- ISBN-13: 9783030257965
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相關分類:
人工智慧、Data-visualization
海外代購書籍(需單獨結帳)
相關主題
商品描述
This book presents the fundamentals and advances in the field of data visualization and knowledge engineering, supported by case studies and practical examples. Data visualization and engineering has been instrumental in the development of many data-driven products and processes. As such the book promotes basic research on data visualization and knowledge engineering toward data engineering and knowledge.
Visual data exploration focuses on perception of information and manipulation of data to enable even non-expert users to extract knowledge. A number of visualization techniques are used in a variety of systems that provide users with innovative ways to interact with data and reveal patterns. A variety of scalable data visualization techniques are required to deal with constantly increasing volume of data in different formats.
Knowledge engineering deals with the simulation of the exchange of ideas and the development of smart information systems in which reasoning and knowledge play an important role.
Presenting research in areas like data visualization and knowledge engineering, this book is a valuable resource for students, scholars and researchers in the field.
Each chapter is self-contained and offers an in-depth analysis of real-world applications. It discusses topics including (but not limited to) spatial data visualization; biomedical visualization and applications; image/video summarization and visualization; perception and cognition in visualization; visualization taxonomies and models; abstract data visualization; information and graph visualization; knowledge engineering; human-machine cooperation; metamodeling; natural language processing; architectures of database, expert and knowledge-based systems; knowledge acquisition methods; applications, case studies and management issues: data administration issues and knowledge; tools for specifying and developing data and knowledge bases using tools based on communication aspects involved in implementing, designing and using KBSs in cyberspace; Semantic Web.
商品描述(中文翻譯)
這本書介紹了資料視覺化和知識工程領域的基本原理和進展,並以案例研究和實際範例作為支持。資料視覺化和工程在許多以資料為驅動的產品和流程的發展中發揮了重要作用。因此,本書促進了對資料視覺化和知識工程的基礎研究,朝向資料工程和知識的方向發展。
視覺資料探索專注於資訊的感知和資料的操作,使得即使是非專業用戶也能提取知識。多種視覺化技術被應用於各種系統中,為用戶提供創新的方式來與資料互動並揭示模式。隨著不同格式的資料量不斷增加,需要各種可擴展的資料視覺化技術來應對這一挑戰。
知識工程則涉及思想交流的模擬和智能資訊系統的開發,其中推理和知識扮演著重要角色。
本書在資料視覺化和知識工程等領域呈現研究成果,是學生、學者和研究人員的寶貴資源。
每一章都是獨立的,並提供對現實應用的深入分析。它討論的主題包括(但不限於)空間資料視覺化;生物醫學視覺化及其應用;影像/視頻摘要和視覺化;視覺化中的感知和認知;視覺化分類法和模型;抽象資料視覺化;資訊和圖形視覺化;知識工程;人機合作;元建模;自然語言處理;資料庫、專家系統和基於知識系統的架構;知識獲取方法;應用、案例研究和管理問題:資料管理問題和知識;使用基於通訊方面的工具來指定和開發資料和知識庫的工具,這些工具涉及在網路空間中實施、設計和使用知識基礎系統(KBSs);語意網。