摘要翻译:
随着本体的激增和自动推理器的强大,敏感信息的保护问题变得更加严重。特别是,由于事实可以从其他事实中推断出来,所以包含在本体论中的信息,尽管本身并不被认为是敏感的,但也越来越有可能被用来推断其他敏感的信息。我们首先考虑测试本体是否安全的问题,定义为它不能被用来使用给定的推理规则集合导出任何敏感的事实。然后,我们考虑了优化本体的问题,该问题基于使尽可能多的有用信息可用而不暴露任何敏感事实的准则。
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英文标题:
《Safe Reasoning Over Ontologies》
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作者:
Genady Grabarnik, Aaron Kershenbaum (IBM TJ Watson Research)
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最新提交年份:
2009
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分类信息:
一级分类:Computer Science 计算机科学
二级分类:Artificial Intelligence 人工智能
分类描述:Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域,除了视觉、机器人、机器学习、多智能体系统以及计算和语言(自然语言处理),这些领域有独立的学科领域。特别地,包括专家系统,定理证明(尽管这可能与计算机科学中的逻辑重叠),知识表示,规划,和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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一级分类:Computer Science 计算机科学
二级分类:Data Structures and Algorithms 数据结构与算法
分类描述:Covers data structures and analysis of algorithms. Roughly includes material in ACM Subject Classes E.1, E.2, F.2.1, and F.2.2.
涵盖数据结构和算法分析。大致包括ACM学科类E.1、E.2、F.2.1和F.2.2中的材料。
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英文摘要:
As ontologies proliferate and automatic reasoners become more powerful, the problem of protecting sensitive information becomes more serious. In particular, as facts can be inferred from other facts, it becomes increasingly likely that information included in an ontology, while not itself deemed sensitive, may be able to be used to infer other sensitive information. We first consider the problem of testing an ontology for safeness defined as its not being able to be used to derive any sensitive facts using a given collection of inference rules. We then consider the problem of optimizing an ontology based on the criterion of making as much useful information as possible available without revealing any sensitive facts.
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PDF链接:
https://arxiv.org/pdf/0904.0228