Tractable NAT-Modeled Bayesian Networks and Privacy Sensitive Construction of Agent Organizations

易处理的 NAT 模型贝叶斯网络和代理组织的隐私敏感构建

• 批准号: RGPIN-2017-03715
• 负责人: Xiang, Yang
• 金额: $ 1.46万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=635080
• 关键词: Tractable; NAT; Modeled; Bayesian; Networks

(1) Rigid, simplistic rules are often used for decision making in personal and mobile devices. For example, a phone number may be placed on a black list, due to report of a spam call from it, causing future calls from the number to be filtered. The rule ignores the possibility that the report may itself be a spam, leading to undesirable actions. Bayesian Networks (BNs), knowledge based systems capable of weighing complex context information, can aid users with more intelligent decisions. Since inference in general BNs is intractable, it is necessary to identify subclasses of BNs that enable efficient inference. They include BNs of low treewidth, and BNs of high treewidth but encoding Context-Specific Independence (CSI) in local structures and being compiled into Arithmetic Circuits or Sum-Product Networks.

(1)在个人和移动设备中，决策经常使用僵化、简单化的规则。例如，一个电话号码可能会因为报告来自该号码的垃圾电话而被放在黑名单上，从而导致来自该号码的未来呼叫被过滤。该规则忽略了报告本身可能是垃圾邮件，从而导致不良行为的可能性。贝叶斯网络(BNS)是一种基于知识的系统，能够权衡复杂的上下文信息，可以帮助用户做出更智能的决策。由于一般BN的推理是难以处理的，因此有必要识别能够实现有效推理的BN的子类。它们包括低树宽的BN和高树宽但在局部结构中编码上下文特定独立性(CSI)并被编译成算术电路或和积网络的BN。