INTERPRETOR: A Software Architecture for the Interpretation of Large and Noisy Data Sets
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Abstract
In many domains there is a need to interpret the high volumes of noisy data. In this paper we propose and describe a new software architecture called INTERPRETOR for summarising and interpreting voluminous high frequency noisy data. INTERPRETOR consists of 3 modules: Filter which processes noise; Abstraction which abstracts features from the filtered data; and Interpretation which takes the abstractions and provides an interpretation of the data. In this seminal article we also show how INTERPRETOR has successfully been applied to 2 case studies.
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How to Cite
Salatian, A. (2011). INTERPRETOR: A Software Architecture for the Interpretation of Large and Noisy Data Sets. INFOCOMP Journal of Computer Science, 10(2), 44–52. Retrieved from https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/333
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