NDLI: Intelligently creating and recommending reusable reformatting rules

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Intelligently creating and recommending reusable reformatting rules

Content Provider	ACM Digital Library
Author	Myers, Brad Shaw, Mary Scaffidi, Christopher
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.
Starting Page	297
Ending Page	306
Page Count	10
File Format	PDF
ISBN	9781605581682
DOI	10.1145/1502650.1502692
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-02-08
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Spreadsheets Consistent data format End-user programming
Content Type	Text
Resource Type	Article

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