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Using Structured Knowledge Representation for Context-Sensitive Probabilistic Modeling

机译：利用结构化知识表示进行上下文敏感概率建模

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摘要

We propose a context-sensitive probabilistic modeling system (COSMOS) that reasons about a complex, dynamic environment through a series of applications of smaller, knowledge-focused models representing contextually relevant information. COSMOS uses a failure-driven architecture to determine whether a context is supported and consequently whether the current model remains applicable. The individual models are specified through sets of structured, hierarchically organized probabilistic logic statements using transfer functions that are then mapped into a representation supporting stochastic inferencing. We demonstrate COSMOS using data from a mechanical pump system.

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作者
Sakhanenko, N. A.; Luger, G. F.;
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年度 2008
页码 p.1-30
总页数 30
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
Transfer functions; Diagnosis(General); Models; Stochastic processes; Logic; Pumps; Symposia; Algorithms;

机译：传递函数;诊断（一般）;模型;随机过程;逻辑;泵;专题讨论会;算法;

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1. Semi-automatic knowledge extraction, representation and context-sensitive intelligent retrieval of video content using collateral context modelling with scalable ontological networks [J] . Atta Badii, Chattun Lallah, Meng Zhu, Signal Processing. Image Communication: A Publication of the the European Association for Signal Processing . 2009,第9期

机译：使用可扩展本体网络的并行上下文建模，对视频内容进行半自动知识提取，表示和上下文敏感的智能检索
2. ANSWERING QUERIES FROM CONTEXT-SENSITIVE PROBABILISTIC KNOWLEDGE BASES [J] . Ngo L., Haddawy P. Theoretical computer science . 1997,第1a2期

机译：从上下文敏感的概率知识库中回答查询
3. Representation, Propagation, and Interpretation of Uncertain Knowledge in Dynamic Probabilistic Material Flow Models [J] . Bornhoeft Nikolaus A., Nowack Bernd, Hilty Lorenz M. Environmental Modeling & Assessment . 2021,第5期

机译：在动态概率材料流模型中不确定知识的表示，传播和解释
4. Using Belief Change Principles for Evolving Bayesian Network Structures in Probabilistic Knowledge Representations [C] . Edgar Jembere, Sibusiso S. Xulu IEEE/WIC/ACM International Conference on Web Intelligence . 2016

机译：使用信念变化原理在概率知识表示中发展贝叶斯网络结构
5. Modeling Content and Users: Structured Probabilistic Representation and Scalable Online Inference Algorithms. [D] . Ahmed, Amr. 2011

机译：建模内容和用户：结构化的概率表示和可扩展的在线推理算法。
6. Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization [O] . Koichi Kobayashi, Kunihiko Hiraishi -1

机译：使用模型检查和多项式优化的上下文敏感概率布尔网络的验证和最优控制
7. Using Structured Knowledge Representation for Context-Sensitive Probabilistic Modeling [O] . Nikita A. Sakhanenko A, George F. Luger B 2012

机译：利用结构化知识表示进行上下文敏感概率建模

Using Structured Knowledge Representation for Context-Sensitive Probabilistic Modeling

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