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Skip to Search Results- 27Natural Language Processing
- 10Machine Learning
- 5Artificial Intelligence
- 3Anagrams
- 3NLP
- 3Reinforcement Learning
- 1Alexander, Graham
- 1Campbell, Hazel V
- 1Chapman, Judy Anne Callie.
- 1Costello, Jeremy
- 1Cowper, Donald Walter.
- 1Dhankar, Abhishek
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Fall 2021
The management of project documentation involves processing a large amount of important information embedded in different contract and project specification documents. Although contract-related documentation is critical for effective information flow and—in turn—successful project management, it...
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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 2023
This thesis introduces a new approach for grounding concepts to vision using visual descriptions, which are text-based descriptions of visual attributes. We hypothesize that these descriptions can enhance the grounding of concepts to vision, thereby improving performance in vision-language tasks....
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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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Application of Natural Language Processing and Information Retrieval in Two Software Engineering Tools
DownloadFall 2021
Many software engineering problems have traditionally been approached by applying techniques based on static analysis and fixed sets of rules. I created two novel techniques to tackle three software engineering problems: typo location, fix suggestion, and crash report bucket creation. However,...
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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 2023
Explainable artificial intelligence models are becoming increasingly important as restrictions grow for corporate use of blackbox models whose predictions affect people’s lives and yet cannot be interpreted. Black boxes do not convey trust to end-users and are difficult to train and debug for...
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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...