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Formatting by Demonstration: An Interactive Machine Learning Approach

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 86 - Number 18
Year of Publication: 2014
Authors:
Kesler Tanner
Christophe Giraud-carrier
Dan R. Olsen Jr.
10.5120/15090-3080

Kesler Tanner, Christophe Giraud-carrier and Dan Olsen R Jr.. Article: Formatting by Demonstration: An Interactive Machine Learning Approach. International Journal of Computer Applications 86(18):41-47, January 2014. Full text available. BibTeX

@article{key:article,
	author = {Kesler Tanner and Christophe Giraud-carrier and Dan R. Olsen Jr.},
	title = {Article: Formatting by Demonstration: An Interactive Machine Learning Approach},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {86},
	number = {18},
	pages = {41-47},
	month = {January},
	note = {Full text available}
}

Abstract

Many routine formatting tasks are subject to patterns. This is especially true of formatting actions performed by users in Excel. Excel has built-in functionality to perform some of these tasks, however their application requires the user to explicitly define logical rules. We show that by using interactive machine learning techniques, such patterns can be learned automatically by iteratively analyzing actions as they are performed by the user. This decreases the amount of work required of the user, and eliminates the necessity of explicitly defining logical rules. Our results show that many useful formatting patterns can be learned with only a few examples.

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