Ontology Design for Scientific Theories That Make Probabilistic Predictions

Poole, David; Smyth, Clinton; Sharma, Rita

doi:10.1109/mis.2009.15

Cited by 15 publications

(8 citation statements)

References 8 publications

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“…So the Semantic Web with its ontologies should be augmented with extra components in order to reach the Wisdom Web level [Heflin, 2003]. The first step is to integrate the different distributed ontologies or part of them into wisdom knowledge in the sense that was just explained [Beneventano, 2003] [McGuinness, 2009] [Poole, 2009].…”

Section: ) Inconsistent Facts ¬Ki (False)mentioning

confidence: 99%

An Overview of Web Intelligence

Ghonaimy¹

2014

The Egyptian Journal of Language Engineering

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This paper gives an overview of Web intelligence which will enable the current Web to reach the Wisdom level by containing Distributed, Integrated, and Active knowledge. In this case it will be capable of performing tasks like problem solving and questionanswering. In addition, it will be capable of processing and understanding natural languages. Web intelligence draws results from a number of disciplines like: Artificial intelligence, Information technology. Mathematics and Physics, Psychology and Linguistics. The paper covers the following topics: Web evolution and architecture-Topics related to Web intelligence-The Deep Web-Semantic computing and the Semantic Web-The Wisdom Web-Precisiated Natural Language.

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Section: ) Inconsistent Facts ¬Ki (False)mentioning

confidence: 99%

An Overview of Web Intelligence

Ghonaimy¹

2014

The Egyptian Journal of Language Engineering

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“…So the Semantic Web with its ontologies should be augmented with extra components in order to reach the Wisdom Web level [72] . The first step is to integrate the different distributed ontologies or part of them into wisdom knowledge in the sense that was just explained [73][74][75] .…”

Section: Where Is the Wisdom We Have Lost In Knowledge?mentioning

confidence: 99%

An Overview of Web Intelligence

غنيمي¹

2012

JKAU Comp IT Sci

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. This paper gives an overview of Web intelligence which will enable the current Web to reach the Wisdom level by containing Distributed, Integrated, and Active knowledge. In this case it will be capable of performing tasks like problem solving and questionanswering. In addition, it will be capable of processing and understanding natural languages. Web intelligence draws results from a number of disciplines like: Artificial intelligence, Information technology. Mathematics and Physics, Psychology and Linguistics. The paper covers the following topics: Web evolution and architecture, Topics related to Web intelligence, The Deep Web, Semantic computing and the Semantic Web, The Wisdom Web, Precisiated Natural Language.

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“…We have been advocating a structure for ontologies using what are called Aristotelian definitions (Smith, 2003a;Poole et al, 2009), based on the idea of Aristotle (350 B.C.) that each class should be described in terms of a super-class (the genus) and the attributes (the differentia) that differentiate this class from other subclasses of the genus.…”

Section: Ontologiesmentioning

confidence: 99%

Foundations of model construction in feature-based semantic science

Poole

2012

Journal of Logic and Computation

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The aim of what semantic science is to have scientific ontologies, data, and hypotheses represented and published in machine understandable forms that enable predictions on new cases. There is much work on developing scientific ontologies and representing scientific data in terms of these ontologies. The next step is to publish hypotheses that can make (probabilistic) predictions on the published data and can be used for prediction on new cases. The published data can be used to evaluate hypotheses. To make a prediction in a particular case, hypotheses are combined to form models. This paper considers feature-based semantic science where the data and new cases are described in terms of features. A prediction for a new case is made by building a model made up of hypotheses that fit together, are consistent with the ontologies used, and are adequate for the case. We give some desiderata for such models, and show how the construction of such models is a form of abduction. We provide a definition for models that satisfies these criteria and prove that it produces a coherent probability distribution over the values of interest.

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Ontology Design for Scientific Theories That Make Probabilistic Predictions

Cited by 15 publications

References 8 publications

An Overview of Web Intelligence

An Overview of Web Intelligence

An Overview of Web Intelligence

Foundations of model construction in feature-based semantic science

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