INTERPRETOR: A Software Architecture for the Interpretation of Large and Noisy Data Sets - Salatian, Apkar (INFOCOMP Journal of Computer Science, 2011)
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.