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Skip to Search Results- 22Natural Language Processing
- 8Machine Learning
- 5Artificial Intelligence
- 2Information Extraction
- 2Misinformation
- 2NLP
- 1Alexander, Graham
- 1Campbell, Hazel V
- 1Dhankar, Abhishek
- 1Dziri, Nouha
- 1Farruque, Nawshad
- 1Hauer, Bradley
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Fall 2009
Answer typing is an important aspect of the question answering process. Most commonly addressed with the use of a fixed set of possible answer classes via question classification, answer typing influences which answers will ultimately be selected as correct. Answer typing introduces the concept...
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Spring 2015
This work is concerned with the problem of extracting structured information networks from a text corpus. The nodes of the network are recognizable entities, typically people, locations, or organizations, while the edges denote relations among such entities. We use state-of-the-art natural...
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Spring 2016
Algorithmic decipherment is a prime example of a truly unsupervised problem. This thesis presents several algorithms developed for the purpose of decrypting unknown alphabetic scripts representing unknown languages. We assume that symbols in scripts which contain no more than a few dozen unique...
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Fall 2016
The field of biomedicine is reeling from “information overload”. Indeed, biomedical researchers find it almost impossible to stay current with published literature due to the vast amounts of data being generated and published. As a result, they are turning to text mining. Over the past two...
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Spring 2016
Morphologically complex languages such as Arabic pose several challenges in Natural Language Processing (NLP) due to their complexity and token sparsity. Most techniques approach the problem by transforming the words of the language from their sparse surface form representation to a less sparse...
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Fall 2017
Inflectional morphology presents numerous problems for traditional computational models, not least of which is an increase in the number of rare types in any corpus. Although few annotated corpora exist for morphologically complex languages, it is possible for lay-speakers of the language to...
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Fall 2018
Information extraction (IE) is one of the most important technologies in the information age. Applying information extraction to text is linked to the prob- lem of text simplification in order to create a structured view of the informa- tion present in free text. However, information extraction...
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Fall 2018
Neural approaches to sequence labeling often use a Conditional Random Field (CRF) to model their output dependencies, while Recurrent Neural Networks (RNN) are used for the same purpose in other tasks. We set out to establish RNNs as an attractive alternative to CRFs for sequence labeling. To do...
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Fall 2019
The conversion of romanized texts back to the native scripts is a challenging task because of the inconsistent romanization conventions and non-standard language use. This problem is compounded by code-mixing, i.e., using words from more than one language within the same discourse. Considering...
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Fall 2020
Language Modeling (LM) is often formulated as a next-word prediction problem over a large vocabulary, which makes it challenging. To effectively perform the task of next-word prediction, Long Short Term Memory networks (LSTMs) must keep track of many types of information. Some information is...