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Method and System for Performing Business Canonical Transformations Disclosure Number: IPCOM000235518D
Publication Date: 2014-Mar-05
Document File: 7 page(s) / 179K

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The Prior Art Database


A method and system is disclosed for performing business canonical transformations. The method and system identifies a suitable transformation to be applied to a dataset and infer information about the dataset.

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Method and System for Performing Business Canonical Transformations

Disclosed is a method and system for performing business canonical transformations .

The method and system suggests a transformation of an unseen data to a training business data that is well characterized with a proper model representation . Here, the training business data is termed as canonical space. Thereafter, a mapping is performed for the unseen data with preservation of some predefined structures that are associated with the unseen data.

The transformation is either sold or used to infer information about the unseen data . Here, the information corresponds to, but is not limited to, origin of the unseen data and similarity with other data sets. In a scenario, the unseen data is mapped across different domains such as financial and analytics .

Fig. 1 illustrates a flowchart of the method for performing the business canonical transformations.


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Figure 1

As shown in the fig. 1, the method begins by obtaining models and transformations . Thereafter, the method obtains the unseen data or a corresponding dataset . In the subsequent steps, the method applies transformation to the dataset and quantifies a difference between an ability to transform the dataset , transformation results and a corresponding model. After quantifying the difference, the method identifies the best matching transformation for the dataset .

Additionally, the method derives a model by characterizing the transformation applied to


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the dataset and determines which transformation applied to the dataset matches a specific model. For instance, the method characterizes the dataset by obtaining a model M, transformations T1 and T2, and a dataset D. Thereafter, the method calculates which of T1 or T2 best modifies dataset D to match model M .

Fig. 2 illustrates the method of mapping the dataset with a specific model .

Figure 2

As shown in fig.2, the left block represents the dataset which is mapped to a mode...