ACM Home Page
Please provide us with feedback. Feedback
Intelligently creating and recommending reusable reformatting rules
Full text PdfPdf (630 KB)
Source
International Conference on Intelligent User Interfaces archive
Proceedings of the 13th international conference on Intelligent user interfaces table of contents
Sanibel Island, Florida, USA
SESSION: Intelligent assistants table of contents
Pages 297-306  
Year of Publication: 2009
ISBN:978-1-60558-168-2
Authors
Christopher Scaffidi  Carnegie Mellon University, Pittsburgh, PA, USA
Brad Myers  Carnegie Mellon University, Pittsburgh, PA, USA
Mary Shaw  Carnegie Mellon University, Pittsburgh, PA, USA
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 13,   Downloads (12 Months): 81,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1502650.1502692
What is a DOI?

ABSTRACT

When users combine data from multiple sources into a spreadsheet or dataset, the result is often a mishmash of different formats, since phone numbers, dates, course numbers and other string-like kinds of data can each be written in many different formats. Although spreadsheets provide features for reformatting numbers and a few specific kinds of string data, they do not provide any support for the wide range of other kinds of string data encountered by users. We describe a user interface where a user can describe the formats of each kind of data. We provide an algorithm that uses these formats to automatically generate reformatting rules that transform strings from one format to another. In effect, our system enables users to create a small expert system called a "tope" that can recognize and reformat instances of one kind of data. Later, as the user is working with a spreadsheet, our system recommends appropriate topes for validating and reformatting the data. With a recall of over 80% for a query time of under 1 second, this algorithm is accurate enough and fast enough to make useful recommendations in an interactive setting. A laboratory experiment shows that compared to manual typing, users can reformat sample spreadsheet data more than twice as fast by creating and using topes.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
 
3
 
4
Fisher II, M., and Rothermel, G. The EUSES Spreadsheet Corpus: A Shared Resource for Supporting Experimentation with Spreadsheet Dependability Mechanisms. Tech. Rpt. 04-12-03, Univ. Nebraska-Lincoln, 2004.
 
5
 
6
 
7
 
8
Marsh, E., and Perzanowski, D. MUC-7 Evaluation of IE Technology: Overview of Results. 7th Message Understanding Conf., 2001.
9
 
10
Mosteller, F., and Youtz, C. Quantifying Probabilistic Expressions. Statistical Science, 5, 1, 1990, 2--12.
11
 
12
Scaffidi, C. Unsupervised Inference of Data Formats in Human-Readable Notation. Proc. 9th Intl. Conf. Enterprise Information Systems, 2007, 236--241.
 
13
Scaffidi, C., Myers, B., and Shaw, M. Fast, Accurate Creation of Data Validation Formats by End-User Developers. Submitted to 2nd Intl. Symp. End-User Development.
14
 
15
Zadeh, L. Fuzzy Logic. Tech Rpt. CSLI-88-116, Stanford University, 1988.

Collaborative Colleagues:
Christopher Scaffidi: colleagues
Brad Myers: colleagues
Mary Shaw: colleagues