Semantic-Based Fuzzy Reasoning for Compliance Auditing

F. Yip, A. K. K. Wong, N. Parameswaran, P. Ray
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引用次数: 4

Abstract

Compliance Management (CM) is increasingly becoming a burden for many organizations due to its cumbersome and labor intensive process. As a result, many experts agree that compliance should be automated as much as possible. Recent efforts in agent based and semantic driven compliance management (CM) are being actively explored in an attempt to tackle challenges in compliance automation. Ontologies and semantic web rules are the fundamental and enabling tools that facilitate the application of compliance automation. In this paper, we discuss the challenges of compliance management, recap on a semantic-based approach discussed in our existing works and highlight the requirements for fuzzy support. Fuzzy extensions are then proposed to enhance the support for intelligent reasoning with uncertain and missing information through the use of Weighted Fuzzy Production Rules (WFPR) and Fuzzy Petri Nets (FPN).
基于语义的符合性审计模糊推理
法规遵从管理(CM)由于其繁琐和劳动密集型的过程,正日益成为许多组织的负担。因此,许多专家都认为遵从性应该尽可能地自动化。最近在基于代理和语义驱动的法规遵循管理(CM)方面的努力正在积极探索,试图解决法规遵循自动化中的挑战。本体和语义web规则是促进遵从性自动化应用的基础和支持工具。在本文中,我们讨论了法规遵循管理的挑战,回顾了我们现有工作中讨论的基于语义的方法,并强调了模糊支持的需求。然后提出模糊扩展,通过使用加权模糊产生规则(WFPR)和模糊Petri网(FPN)来增强对不确定和缺失信息的智能推理的支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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