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The Folksodriven framework makes it possible for data scientists to define anontology environment where searching for buried patterns that have some kind ofpredictive power to build predictive models more effectively. It accomplishesthis through an abstractions that isolate parameters of the predictive modelingprocess searching for patterns and designing the feature set, too. To reflectthe evolving knowledge, this paper considers ontologies based on folksonomiesaccording to a new concept structure called "Folksodriven" to representfolksonomies. So, the studies on the transformational regulation of theFolksodriven tags are regarded to be important for adaptive folksonomiesclassifications in an evolving environment used by Intelligent Systems torepresent the knowledge sharing. Folksodriven tags are used to categorizesalient data points so they can be fed to a machine-learning system and"featurizing" the data.

Automatic Data Deformation Analysis on Evolving Folksonomy Driven Environment