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ReferencesNavigation arrowAuthorsNavigation arrowJerry Talton
May 23

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Jerry Talton

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2012
 
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Talton, Jerry, Yang, Lingfeng, Kumar, Ranjitha, Lim, Maxine, Goodman, Noah and Mech, Radomír (2012): Learning design patterns with Bayesian grammar induction. In: Proceedings of the 2012 ACM Symposium on User Interface Software and Technology 2012. pp. 63-74.

“Design patterns have proven useful in many creative fields, providing content creators with archetypal, reusable guidelines to leverage in projects. Creating such patterns, however, is a time-consuming, manual process, typically relegated to a few experts in any given domain. In this paper, we describe an algorithmic method for learning design patterns directly from data using techniques from natural language processing and structured concept learning. Given a set of labeled, hierarchical designs as input, we induce a probabilistic formal grammar over these exemplars. Once learned, this grammar encodes a set of generative rules for the class of designs, which can be sampled to synthesize novel artifacts. We demonstrate the method on geometric models and Web pages, and discuss how the learned patterns can drive new interaction mechanisms for content creators.”

© All rights reserved Talton et al. and/or ACM Press

 
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May 23

“ Knowledge is commonly socially constructed, through collaborative efforts towards shared objectives or by dialogues and challenges brought about by different persons' perspectives. ”

-- G. Salomon (in "Distributed Cognitions: Psychological and Educational Considerations")

 
 

Featured chapter

Read the fascinating history of Wearable Computing, told by its father, Steve Mann

Read Steve's chapter !

 
 

Help us help you!

 
 
 
 
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