Learning text editing tasks from examples: a procedural approach
Titel:
Learning text editing tasks from examples: a procedural approach
Auteur:
Mo, Dan H. Witten, Ian H.
Verschenen in:
Behaviour & information technology
Paginering:
Jaargang 11 (1992) nr. 1 pagina's 32-45
Jaar:
1992-01-01
Inhoud:
Reformatting blocks of semi-structured information is a common editing task that typically involves highly repetitive action sequences, but ones where exceptional cases arise constantly and must be dealt with as they arise. This paper describes a procedural programming-by-example approach to repetitive text editing which allows users to construct programs within a standard editing interface and extend them incrementally. Following a brief practice period during which they settle on an editing strategy for the task at hand, users commence editing in the normal way. Once the first block of text has been edited, they inform the learning system which constructs a generalized procedure from the actions that have been recorded. The system then attempts to apply the procedure to the next block of text, by predicting editing actions and displaying them for confirmation. If the user accepts a prediction, the action is carried out (and the program may be generalized accordingly); otherwise the user is asked to intervene and supply additional information, in effect debugging the program on the fly. A pilot implementation is described that operates in a simple interactive point-and-click editor (Macintosh MINI-EDIT), along with its performance on three sample tasks. In one case the procedure was learned correctly from the actions on the first text block, while in the others minor debugging was needed on subsequent text blocks. In each case a much smaller number of both keystrokes and mouse-clicks was required than with normal editing, without the system making any prior assumptions about the stucture of the text except for some general knowledge about lexical patterns. Although a smooth interactive interface has not yet been constructed, the results obtained serve to indicate the potential of this approach for semi-structured editing tasks.
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