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Salman Ahmad

 

Publications by Salman Ahmad (bibliography)

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2011
 
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Kumar, Ranjitha, Talton, Jerry O., Ahmad, Salman and Klemmer, Scott R. (2011): Bricolage: example-based retargeting for web design. In: Proceedings of ACM CHI 2011 Conference on Human Factors in Computing Systems 2011. pp. 2197-2206. Available online

The Web provides a corpus of design examples unparalleled in human history. However, leveraging existing designs to produce new pages is often difficult. This paper introduces the Bricolage algorithm for transferring design and content between Web pages. Bricolage employs a novel, structured-prediction technique that learns to create coherent mappings between pages by training on human-generated exemplars. The produced mappings are then used to automatically transfer the content from one page into the style and layout of another. We show that Bricolage can learn to accurately reproduce human page mappings, and that it provides a general, efficient, and automatic technique for retargeting content between a variety of real Web pages.

© All rights reserved Kumar et al. and/or their publisher

 
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Ahmad, Salman, Battle, Alexis, Malkani, Zahan and Kamvar, Sepander (2011): The Jabberwocky programming environment for structured social computing. In: Proceedings of the 2011 ACM Symposium on User Interface Software and Technology 2011. pp. 53-64. Available online

We present Jabberwocky, a social computing stack that consists of three components: a human and machine resource management system called Dormouse, a parallel programming framework for human and machine computation called ManReduce, and a high-level programming language on top of ManReduce called Dog. Dormouse is designed to enable cross-platform programming languages for social computation, so, for example, programs written for Mechanical Turk can also run on other crowdsourcing platforms. Dormouse also enables a programmer to easily combine crowdsourcing platforms or create new ones. Further, machines and people are both first-class citizens in Dormouse, allowing for natural parallelization and control flows for a broad range of data-intensive applications. And finally and importantly, Dormouse includes notions of real identity, heterogeneity, and social structure. We show that the unique properties of Dormouse enable elegant programming models for complex and useful problems, and we propose two such frameworks. ManReduce is a framework for combining human and machine computation into an intuitive parallel data flow that goes beyond existing frameworks in several important ways, such as enabling functions on arbitrary communication graphs between human and machine clusters. And Dog is a high-level procedural language written on top of ManReduce that focuses on expressivity and reuse. We explore two applications written in Dog: bootstrapping product recommendations without purchase data, and expert labeling of medical images.

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

 
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