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A Context Centric Model for building a Knowledge advantage Machine Based on Personal Ontology Patterns.

机译:基于个人本体模式构建知识优势机器的上下文中心模型。

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摘要

Throughout the industrial era societal advancement could be attributed in large part to introduction a plethora of electromechanical machines all of which exploited a key concept known as Mechanical Advantage. In the post-industrial era exploitation of knowledge is emerging as the key enabler for societal advancement. With the advent of the Internet and the Web, while there is no dearth of knowledge, what is lacking is an efficient and practical mechanism for organizing knowledge and presenting it in a comprehensible form appropriate for every context. This is the fundamental problem addressed by my dissertation.;We begin by proposing a novel architecture for creating a Knowledge Advantage Machine (KaM), one which enables a knowledge worker to bring to bear a larger amount of knowledge to solve a problem in a shorter time. This is analogous to an electromechanical machine that enables an industrial worker to bring to bear a large amount of power to perform a task thus improving worker productivity. This work is based on the premise that while a universal KaM is beyond the realm of possibility, a KaM specific to a particular type of knowledge worker is realizable because of the limited scope of his/her personal ontology used to organize all relevant knowledge objects.;The proposed architecture is based on a “society of intelligent agents" which collaboratively discover, markup, and organize relevant knowledge objects into a semantic knowledge network on a continuing basis. This in-turn is exploited by another agent known as the Context Agent which determines the current context of the knowledge worker and makes available in a suitable form the relevant portion of the semantic network. In this dissertation we demonstrate the viability and extensibility of this architecture by building a prototype KaM for one type of knowledge worker such as a professor.
机译:在整个工业时代,社会进步在很大程度上可以归因于引入了许多机电设备,所有这些机电设备都利用了称为“机械优势”的关键概念。在后工业时代,对知识的利用正逐渐成为促进社会进步的关键因素。随着Internet和Web的到来,虽然没有知识的匮乏,但缺少一种有效且实用的机制来组织知识并以适合每种情况的可理解形式呈现知识。这是我的论文要解决的基本问题。;我们首先提出一种新颖的架构来创建知识优势机器(KaM),该架构使知识工作者能够携带更多的知识以在较短的时间内解决问题。时间。这类似于使机械工人能够承受大量电力来执行任务的机电机械,从而提高了工人的生产率。这项工作的前提是,尽管通用KaM超出了可能性范围,但由于用于组织所有相关知识对象的个人本体的范围有限,因此可以实现针对特定类型知识工作者的KaM。 ;所提出的体系结构是基于“智能代理社会”的,该组织不断地发现,标记和组织相关知识对象,并将其组织到语义知识网络中,进而被称为上下文代理的另一种代理利用。确定知识工作者的当前上下文,并以合适的形式提供语义网络的相关部分。本文我们通过为一种类型的知识工作者(如教授)构建原型KaM来证明该体系结构的可行性和可扩展性。

著录项

  • 作者

    Wang, Luyi.;

  • 作者单位

    West Virginia University.;

  • 授予单位 West Virginia University.;
  • 学科 Artificial Intelligence.;Computer Science.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 104 p.
  • 总页数 104
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:43:41

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