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Data Analytics by Learning and Exploration
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Description
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DALE is an extension of the Wings workflow system that enables end users with no background in machine learning to analyze data by applying complex state-of-the-art techniques captured as workflows. DALE includes a library of workflows and software components for data analytics, notably for document classification, document clustering, and topic extraction. DALE has been used by non-experts including students at the high-school level.
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Status
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The DALE framework currently has focused to date on workflows for text analytics tasks such as document classification, document clustering, and topic modeling. These workflows are composed of workflow fragments that pre-process text, prepare the data, and set up the learning task.
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Research
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We plan to extend DALE so that end users will be able to acquire advanced analytic skills through practice in several domains of broad interest.
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Publications
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- A Framework for Efficient Text Analytics through Automatic Configuration and Customization of Scientific Workflows, Matheus Hauder, Yolanda Gil, Yan Liu. In Proceedings of the Seventh IEEE International Conference on e-Science, Stockholm, Sweden, 2011
- Making Data Analysis Expertise Broadly Accessible through Workflows, Matheus Hauder, Yolanda Gil, Ricky Sethi, Yan Liu, Hyunjoon Jo. To appear in Proceedings of the Sixth Workshop on Workflows in Support of Large-Scale Science (WORKS'11), held in conjunction with SC 2011, Seattle, Washington, 2011
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Demo
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See a demo -->
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People
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Group Members:
Collaborators:
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Funding
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- National Science Foundation (NSF)
- National Science Foundation (NSF)
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Links
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