Article Title

From Data to Wisdom: The Progression of Computational Learning in Text Mining

Authors

Robert P. Schumaker, Cleveland State University

Abstract

The DIKW hierarchy has long been a standard framework with which researchers can differentiate between levels of what they see and know. However much of the research conducted explores the nuances and precise divisions between each hierarchy level and assumes that the user will know how to use them. We plan to restrict our study to textual Web documents and propose a framework extension to the DIKW hierarchy that encompasses acquisition, delivery and prediction elements. We feel that such an extension can help better define each level of the DIKW hierarchy into discrete units that can be applied to the content contained within the Internet.

Recommended Citation

Schumaker, Robert P. (2011) "From Data to Wisdom: The Progression of Computational Learning in Text Mining," Communications of the IIMA: Vol. 11: Iss. 1, Article 4.
DOI: https://doi.org/10.58729/1941-6687.1155
Available at: https://scholarworks.lib.csusb.edu/ciima/vol11/iss1/4