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VisComplete: Automating Suggestions for Visualization Pipelines

VisComplete: Automating Suggestions for Visualization Pipelines

da仔
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In this paper, we propose techniques to help users construct pipelines by consensus—automatically suggesting completions based on a database of previously created pipelines. In particular, we compute correspondences between existing pipeline subgraphs from the database, and use these to predict sets of likely pipeline additions to a given partial pipeline. By presenting these predictions in a carefully designed interface, users can create visualizations and other data products more efficiently because they can augment their normal work patterns with the suggested completions.
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