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Integrating Semantic Annotations in Bayesian Causal Models
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由 HG Ceballos 著作被引用 10 次 — Having annotations over causal model variables enables matching variables among different causal models and calculating a distributed causal effect[2] through.
Integrating Semantic Annotations in Bayesian Causal ...
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We propose a Semantic Bayesian Causal Model (SBCM) that is an extension of a Bayesian causal model with a semantic layer for representing causal ...
Integrating Semantic Annotations in Bayesian Causal Models
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This work needs means to represent the context on which the causal model is developed and the meaning of causal model events in the real world when the ...
Integrating Semantic Annotations in Bayesian Causal Models
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I argue that solving the interpretive problem requires coming up with a new semantics for Bayesian inference. I present and contrast two solutions to the ...
Integrating semantic annotations in bayesian causal models
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This result offers an appealing explanation for the usefulness of causal information and links our explicitly dynamic approach to more static causal ...
Integrating Semantic Annotations in Bayesian Causal Models
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Héctor G. Ceballos Cancino - Google 学术搜索
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Integrating Semantic Annotations in Bayesian Causal Models. HG Ceballos, FJC Ortiz. Description Logics, 2007. 10, 2007. A knowledge-based entrepreneurial ...
Annotated Bayesian Networks: A Tool to Integrate Textual ...
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2024年10月22日 — This paper presents an ontology-based semantic search method, referred to as influential SemSim (i-SemSim), which relies on the Bayesian ...
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... Causal Agents, a methodology and agent architecture for modeling intelli- gent agents based on Causality Theory. We draw upon concepts from classical ...
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Héctor G. Ceballos Cancino - Google Acadêmico
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Integrating Semantic Annotations in Bayesian Causal Models. HG Ceballos, FJC Ortiz. Description Logics, 2007. 10, 2007. A knowledge-based entrepreneurial ...
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