知识处理系统的体系结构

V. B. Lawrence, S. Ahamed
{"title":"知识处理系统的体系结构","authors":"V. B. Lawrence, S. Ahamed","doi":"10.1109/CN.1996.534636","DOIUrl":null,"url":null,"abstract":"We start with three basic notions: that knowledge is based on concepts; that events enhance or refute such concepts; and that no concept or its modifications is absolute. Within this framework, we build a processing system that is dynamic based on the knowledge available, aware of current events that are modifying the knowledge base with some finite probability that its result is accurate. In a sense the system is limited by its capacity to store/retrieve information (knowledge), its ability to (intelligently) process information, and its ability to compute the confidence level with which it has generated the previous step(s). We fall back on database facilities for storing/retrieving information, on AI techniques for processing and on basic probability (fuzzy set) theory to numerically compute or at least estimate the accuracy of its discrete steps. Whereas any computer system with a complex software structure can serve as a knowledge machine, we present an architecture which stores/retrieves information; processes, learns, and modifies the information; and finally computes or estimates the confidence level in each step or procedure. These are the macro instructions to the rather elaborate hardware. It processes in two dimensions: the knowledge domain (i.e. generates conclusions) and the numeric domain (i.e. generates confidence level), confirming the earlier stated notion that the conclusion reached so far is not undeniable.","PeriodicalId":217137,"journal":{"name":"3rd International Workshop on Community Networking 1996. Proceedings","volume":"237 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Architecture of a knowledge processing system\",\"authors\":\"V. B. Lawrence, S. Ahamed\",\"doi\":\"10.1109/CN.1996.534636\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We start with three basic notions: that knowledge is based on concepts; that events enhance or refute such concepts; and that no concept or its modifications is absolute. Within this framework, we build a processing system that is dynamic based on the knowledge available, aware of current events that are modifying the knowledge base with some finite probability that its result is accurate. In a sense the system is limited by its capacity to store/retrieve information (knowledge), its ability to (intelligently) process information, and its ability to compute the confidence level with which it has generated the previous step(s). We fall back on database facilities for storing/retrieving information, on AI techniques for processing and on basic probability (fuzzy set) theory to numerically compute or at least estimate the accuracy of its discrete steps. Whereas any computer system with a complex software structure can serve as a knowledge machine, we present an architecture which stores/retrieves information; processes, learns, and modifies the information; and finally computes or estimates the confidence level in each step or procedure. These are the macro instructions to the rather elaborate hardware. It processes in two dimensions: the knowledge domain (i.e. generates conclusions) and the numeric domain (i.e. generates confidence level), confirming the earlier stated notion that the conclusion reached so far is not undeniable.\",\"PeriodicalId\":217137,\"journal\":{\"name\":\"3rd International Workshop on Community Networking 1996. Proceedings\",\"volume\":\"237 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"3rd International Workshop on Community Networking 1996. Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CN.1996.534636\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"3rd International Workshop on Community Networking 1996. Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CN.1996.534636","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

我们从三个基本概念开始:知识是以概念为基础的;事件加强或驳斥了这些概念;没有任何概念或其修正是绝对的。在这个框架内,我们构建了一个基于可用知识的动态处理系统,它知道当前事件正在以有限的概率修改知识库,其结果是准确的。从某种意义上说,系统受到其存储/检索信息(知识)的能力、(智能)处理信息的能力以及计算生成前一步的置信水平的能力的限制。我们依靠数据库设施来存储/检索信息,依靠人工智能技术来处理信息,依靠基本概率(模糊集)理论来数值计算或至少估计其离散步骤的准确性。鉴于任何具有复杂软件结构的计算机系统都可以作为知识机器,我们提出了一种存储/检索信息的体系结构;处理、学习和修改信息;最后计算或估计每个步骤或程序的置信水平。这些是相当复杂的硬件的宏指令。它在两个维度上进行处理:知识领域(即产生结论)和数字领域(即产生置信水平),证实了前面所说的到目前为止得出的结论是不可否认的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Architecture of a knowledge processing system
We start with three basic notions: that knowledge is based on concepts; that events enhance or refute such concepts; and that no concept or its modifications is absolute. Within this framework, we build a processing system that is dynamic based on the knowledge available, aware of current events that are modifying the knowledge base with some finite probability that its result is accurate. In a sense the system is limited by its capacity to store/retrieve information (knowledge), its ability to (intelligently) process information, and its ability to compute the confidence level with which it has generated the previous step(s). We fall back on database facilities for storing/retrieving information, on AI techniques for processing and on basic probability (fuzzy set) theory to numerically compute or at least estimate the accuracy of its discrete steps. Whereas any computer system with a complex software structure can serve as a knowledge machine, we present an architecture which stores/retrieves information; processes, learns, and modifies the information; and finally computes or estimates the confidence level in each step or procedure. These are the macro instructions to the rather elaborate hardware. It processes in two dimensions: the knowledge domain (i.e. generates conclusions) and the numeric domain (i.e. generates confidence level), confirming the earlier stated notion that the conclusion reached so far is not undeniable.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信