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Skip to Search Results- 27Natural Language Processing
- 10Machine Learning
- 5Artificial Intelligence
- 3NLP
- 3Reinforcement Learning
- 2Computational Linguistics
- 1Alexander, Graham
- 1Campbell, Hazel V
- 1Costello, Jeremy
- 1Dhankar, Abhishek
- 1Dziri, Nouha
- 1Farruque, Nawshad
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Vision-assisted behavior-based construction safety: Integrating computer vision and natural language processing
DownloadFall 2023
Background: Construction sites can be hazardous places. Behavior-based safety is a method to optimize workers’ behaviors and improve site safety. Previous behavior-based safety has been criticized for their low efficiency because of manual observation. The community has conducted enormous studies...
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Fall 2020
Distinguishing between homonymy and polysemy can facilitate Word Sense Disambiguation (WSD), as WSD systems use the standard sense inventories that are excessively fine-grained and include many polysemous senses. We classify words as either homonymous or polysemous by building graphs of word...
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Fall 2022
Sentence reconstruction and generation are essential applications in Natural Language Processing (NLP). Early studies were based on classic methods such as production rules and statistical models. Recently, the prevailing models typically use deep neural networks. In this study, we utilize deep...
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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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Spring 2023
Traditional survey based methods for clinical depression detection are not always effective; the patient may not reflect their actual mental health condition because of the cognitive bias exhibited while filling out questionnaires about depression. Established through ample earlier work, social...
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Fall 2022
Medical Fake News is a pervasive part of the information that people consume on the internet. It may lead people to take actions which may put the lives of their family and community in danger - such actions include vaccine hesitancy, administering unverified and harmful treatments, etc. First...
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Spring 2023
Dialogue systems powered by large pre-trained language models exhibit an innate ability to deliver fluent and natural-sounding responses. Despite their impressive performance, these models fail to conduct interesting and consistent exchanges of turns and can often generate factually incorrect...
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Spring 2022
Radiology reports are the primary medium through which physicians communicate findings and diagnoses from patients' medical scans. Examples include radiology reports for chest radiographs, CT scans of the brain, medical reports of retinal images, and more. However, the process of writing medical...
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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 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...