Grouper: a dynamic clustering interface to Web search results
WWW '99 Proceedings of the eighth international conference on World Wide Web
Outlier finding: focusing user attention on possible errors
Proceedings of the 14th annual ACM symposium on User interface software and technology
Multiple selections in smart text editing
Proceedings of the 7th international conference on Intelligent user interfaces
Machine learning for information extraction in informal domains
Machine learning for information extraction in informal domains
Automatic string replace by examples
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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In current text editors, the find & replace command offers only two options: replace one match at a time prompting for confirmation, or replace all matches at once without any confirmation. Both approaches are prone to errors. This paper explores a third way: cluster-based find & replace, in which the matches are clustered by similarity and whole clusters can be replaced at once. We hypothesized that cluster-based find & replace would make find & replace tasks both faster and more accurate, but initial user studies suggest that clustering may improve speed on some tasks but not accuracy. Users also prefer using a perfect-selection strategy for find & replace, rather than an interleaved decision-action strategy.