A Knowledge Representation Practionary: Guidelines Based on Charles Sanders Peirce
暫譯: 知識表示實務指南:基於查爾斯·桑德斯·皮爾斯的指導原則
Michael K. Bergman
- 出版商: Springer
- 出版日期: 2018-12-20
- 售價: $8,670
- 貴賓價: 9.5 折 $8,237
- 語言: 英文
- 頁數: 462
- 裝訂: Hardcover
- ISBN: 3319980912
- ISBN-13: 9783319980911
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商品描述
This major work on knowledge representation is based on the writings of Charles S. Peirce, a logician, scientist, and philosopher of the first rank at the beginning of the 20th century. This book follows Peirce's practical guidelines and universal categories in a structured approach to knowledge representation that captures differences in events, entities, relations, attributes, types, and concepts. Besides the ability to capture meaning and context, the Peircean approach is also well-suited to machine learning and knowledge-based artificial intelligence. Peirce is a founder of pragmatism, the uniquely American philosophy.
Knowledge representation is shorthand for how to represent human symbolic information and knowledge to computers to solve complex questions. KR applications range from semantic technologies and knowledge management and machine learning to information integration, data interoperability, and natural language understanding. Knowledge representation is an essential foundation for knowledge-based AI.
This book is structured into five parts. The first and last parts are bookends that first set the context and background and conclude with practical applications. The three main parts that are the meat of the approach first address the terminologies and grammar of knowledge representation, then building blocks for KR systems, and then design, build, test, and best practices in putting a system together. Throughout, the book refers to and leverages the open source KBpedia knowledge graph and its public knowledge bases, including Wikipedia and Wikidata. KBpedia is a ready baseline for users to bridge from and expand for their own domain needs and applications. It is built from the ground up to reflect Peircean principles.
This book is one of timeless, practical guidelines for how to think about KR and to design knowledge management (KM) systems. The book is grounded bedrock for enterprise information and knowledge managers who are contemplating a new knowledge initiative.
This book is an essential addition to theory and practice for KR and semantic technology and AI researchers and practitioners, who will benefit from Peirce's profound understanding of meaning and context.
商品描述(中文翻譯)
這部關於知識表示的重大著作是基於查爾斯·S·皮爾斯(Charles S. Peirce)的著作,他是20世紀初的邏輯學家、科學家和一流哲學家。本書遵循皮爾斯的實用指導方針和普遍類別,以結構化的方法來進行知識表示,捕捉事件、實體、關係、屬性、類型和概念之間的差異。除了能夠捕捉意義和上下文外,皮爾斯的方法也非常適合機器學習和基於知識的人工智慧。皮爾斯是實用主義的創始人,這是一種獨特的美國哲學。
知識表示是指如何將人類的符號信息和知識表示給計算機,以解決複雜問題。知識表示(KR)應用範圍從語義技術和知識管理、機器學習到信息整合、數據互操作性和自然語言理解。知識表示是基於知識的人工智慧的基本基礎。
本書分為五個部分。第一部分和最後一部分作為書的開頭和結尾,首先設定背景和上下文,最後以實際應用作結。三個主要部分是本書的核心,首先討論知識表示的術語和語法,然後是KR系統的構建模塊,接著是設計、構建、測試和最佳實踐的系統整合。在整個過程中,本書參考並利用開源的KBpedia知識圖譜及其公共知識庫,包括維基百科和Wikidata。KBpedia是用戶從中橋接並擴展其自身領域需求和應用的現成基準,並從基礎開始構建,以反映皮爾斯的原則。
本書是關於如何思考知識表示(KR)和設計知識管理(KM)系統的永恆實用指導方針。這本書是企業信息和知識管理者在考慮新的知識倡議時的堅實基礎。
本書是KR、語義技術和人工智慧研究者及實踐者理論與實踐的重要補充,他們將從皮爾斯對意義和上下文的深刻理解中受益。