CFP last date
20 May 2024
Reseach Article

Formatting by Demonstration: An Interactive Machine Learning Approach

by Kesler Tanner, Christophe Giraud-carrier, Dan R. Olsen Jr.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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, Dan R. Olsen Jr. . Formatting by Demonstration: An Interactive Machine Learning Approach. International Journal of Computer Applications. 86, 18 ( January 2014), 41-47. DOI=10.5120/15090-3080

@article{ 10.5120/15090-3080,
author = { Kesler Tanner, Christophe Giraud-carrier, Dan R. Olsen Jr. },
title = { Formatting by Demonstration: An Interactive Machine Learning Approach },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 86 },
number = { 18 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 41-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume86/number18/15090-3080/ },
doi = { 10.5120/15090-3080 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:04:36.675195+05:30
%A Kesler Tanner
%A Christophe Giraud-carrier
%A Dan R. Olsen Jr.
%T Formatting by Demonstration: An Interactive Machine Learning Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 86
%N 18
%P 41-47
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
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.

References
  1. Contextures. Excel conditional formatting — examples. Online at http://www. contextures. com/xlCondFormat03. html, 2013.
  2. A. Cypher and D. C. Halbert. Watch What I Do: Programming by Demonstration. The MIT Press, 1993.
  3. T. French. Excel conditional formatting. Online at http://spreadsheets. about. com/od/advancedexcel/tp/090822- excel-conditional-formatting-hub. htm, 2013.
  4. S. Gulwani. Automating string processing in spreadsheets using input-output examples. In Proceedings of the 38th Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, pages 317–330, 2011.
  5. S. Harkins. 10 cool ways to use Excel's conditional formatting feature. Online at http://www. techrepublic. com/blog/10things/10-cool-waysto- use-excels-conditional-formatting-feature/3166, 2012.
  6. T. Lau. Programming by Demonstration: A Machine Learning Approach. PhD thesis, Department of Computer Science and Engineering, University of Washington, 2001.
  7. T. Lau, S. A. Wolfram, P. Domingos, and D. S. Weld. Programming by demonstration using version space algebra. Machine Learning, 53(1-2):111–156, 2003.
  8. R. C. Miller. Lightweight Structure in Text. PhD thesis, Computer Science Department, School of Computer Science, Carnegie Mellon University, 2002.
  9. T. Mitchell. Generalization as search. Artificial Intelligence, 18:203–226, 1982.
  10. B. A. Myers. Tourmaline: Text formatting by demonstration. In A. Cypher, editor, Watch What I Do: Programming by Demonstration, chapter 14. The MIT Press, 1993.
  11. C. G. Nevill-Manning. Programming by demonstration. New Zealand Journal of Computing, 4(2):15–24, 1993.
  12. R. Nix. Editing by example. ACM Transactions on Programming Languages and Systems, 7(4):600–621, 1985.
  13. J. R. Quinlan. Inductive learning of decision trees. Machine Learning, 1:81–106, 1986.
  14. K. VanLehn. Felicity conditions for human skill acquisition: Validating an ai-based theory. Technical Report CIS-21, Xerox Corp. , Palo Alto, CA. Palo Alto Research Center, 1983.
  15. I. H. Witten and D. Mo. TELS: Learning text editing tasks from examples. In A. Cypher, editor, Watch What I Do: Programming by Demonstration, chapter 8. The MIT Press, 1993.
Index Terms

Computer Science
Information Sciences

Keywords

Formatting by Demonstration Automatic Task Completion Interactive Machine Learning Excel