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SAS Collaboration Supports Research on Language Models
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The award will run from September 1, 2014 to August 31, 2015.
Abstract – An important problem in Natural Language Processing is creating a robust language model that represents how a set of documents is composed from a set of words. Having a robust language model is critical for many text analytic tasks, including topic modeling, information retrieval, text categorization, and sentiment analysis. Most language models utillize a bag-of-words representation that ignores word order. While these representations suffice for some text analytic tasks, a context-sensitive language model is essential for many tasks such as discovering semantic relationships, question answering, machine translation, and dialog modeling. This project will investigate the effectiveness of leveraging Deep Learning architectures to create context-sensitive language models.
For more information on Dr. Lester, click here.
For more information on Dr. Mott, click here.
~coates~
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