OCCAM: Ontology-Based Computational Contextual Analysis and Modeling

机译：OCCAM：基于本体的计算上下文分析和建模

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The ability to model cognitive agents depends crucially on being able to encode and infer with contextual information at many levels (such as situational, psychological, social, organizational, political levels). We present initial results from a novel computational framework, Coordinated Probabilistic Relational Models (CPRM), that can potentially model the combined impact of multiple contextual information sources for analysis and prediction.

机译：对认知行为者进行建模的能力至关重要地取决于能否在多个级别（例如情境，心理，社会，组织，政治级别）对上下文信息进行编码和推断。我们从一个新颖的计算框架“协调概率关系模型”（CPRM）提出了初步结果，该模型可以潜在地对多个上下文信息源的组合影响进行建模以进行分析和预测。

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《International and Interdisciplinary Conference on Modeling and Using Context(CONTEXT 2007); 20070820-24; Roskilde(DK)》|2007年|P.356-368|共13页
会议地点 Roskilde(DK)
作者
Srini Narayanan; Katie Sievers; Steve Maiorano;
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作者单位

International Computer Science Institute (ICSI) and University of California, Berkeley 1947 Center Street, Berkeley, California 94704;

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会议组织
原文格式 PDF
正文语种 eng
中图分类计算机的应用;
关键词
bayesian modeling; cognitive models; agent models; computational sociology;

机译：贝叶斯建模;认知模型;智能体模型;计算社会学;

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机译：OCCAM：基于本体的计算上下文分析和建模

OCCAM: Ontology-Based Computational Contextual Analysis and Modeling

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