Browse Dept. of Computer Science by Subject "Natural Language Processing"

  • Samdani, Rajhans (2014-01-16)
    Structured prediction describes problems which involve predicting multiple output variables with expressive and complex interdependencies and constraints. Learning over expressive structures (called structural learning) ...

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  • Satapathy, Sidhartha (2019-04-23)
    Despite several instances of societal attention and widespread protests, there is no database of police-involved fatal shootings. To this end, it is extremely important to develop a system that will monitor media reports ...

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  • Jindal, Prateek; Roth, Dan; Kale, Laxmikant V. (2013-12-04)
    Parallel programming is becoming increasingly popular. Computers have increasingly many cores (processors). Also, large computer-clusters are becoming available. But there is still no good programming framework for these ...

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  • Zhong, Zexuan (2019-04-26)
    Translating natural language descriptions into executable programs is a fundamental problem for computational linguistics. Recent research proposes neural-network-based approaches to address the problem. These approaches ...

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  • Schieferstein, Sarah (2018-12-11)
    When using neural models for NLP tasks, like language modelling, it is difficult to utilize a language with little data, also known as a low-resource language. Creole languages are frequently low-resource and as such it ...

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  • Jindal, Prateek (2014-01-16)
    Recent US government initiatives have made available a large number of Electronic Health Records (EHRs). These EHRs contain valuable information which can be used in Clinical Decision Support (CDS). So, Information Extraction ...

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  • Hanneke, Steve; Roth, Dan (2004-06)
    We propose a unified perspective of a large family of semi-supervised learning algorithms, which select and label unlabeled data in an iterative process. We discuss existing approaches that label examples based on the ...

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  • Goldwasser, Dan (2013-02-03)
    In this work we take a first step towards Learning from Natural Instructions (LNI), a framework for communicating human knowledge to computer systems using natural language. In this framework the process of learning is ...

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  • Wieting, John (2014-05-30)
    Lexical entailment is a requirement for success in the domains of Recognizing Textual Entailment (RTE) as well as related tasks like Question-Answering and Information Extraction. Previous approaches tend to fall into two ...

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  • Connor, Michael (2012-02-06)
    A fundamental step in sentence comprehension involves assigning semantic roles to sentence constituents. To accomplish this, the listener must parse the sentence, find constituents that are candidate arguments, and assign ...

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  • Hodosh, Micah A (2015-11-25)
    Automatically describing an image with a concise natural language description is an ambitious and emerging task bringing together the Natural Language and Computer Vision communities. With any emerging task, the necessary ...

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  • Punyakanok, Vasin; Roth, Dan; Yih, Wen-tau (2004-01)
    We describe an approach for answer selection in a free form question answering task. In order to go beyond a key-word based matching in selecting answers to questions, one would like to develop a principled way for the ...

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  • Srikumar, Vivek (2013-05-24)
    The problem of ascribing a semantic representation to text is an important one that can help text understanding problems like textual entailment. In this thesis, we address the problem of assigning a shallow semantic ...

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  • Levine, Geoffrey C. (2012-02-06)
    In order for a machine learning effort to succeed, an appropriate model must be chosen. This is a difficult task in which one must balance flexibility, so that the model can capture the complexities of the domain, and ...

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