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Skip to Search Results- 36Zaiane, Osmar (Computing Science)
- 2Goebel, Randy (Computing Science)
- 1Bolduc, Francois (Pediatrics)
- 1Gross, Douglas (Physical Therapy)
- 1Günther, Johannes (Computing Science)
- 1Hu, Bryan (Electrical and Computer Engineering)
- 2Dziri, Nouha
- 1Abnar, Afra
- 1Adilmagambetov, Aibek
- 1Ahmed, Farrukh
- 1Alam Anik, Md Tanvir
- 1Austin, Eric
- 8Machine Learning
- 6Natural Language Processing
- 3Associative Classification
- 2Association Rules
- 2Community Detection
- 2Community Mining
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Spring 2023
This thesis describes the design of a system that is capable of the generation of a Knowledge Graph (KG), referred to as Knowledge Graph Population (KGP), from conversations, specifically with elderly people. While this system still follows a traditional KGP approach with Entity Recognition (ER),...
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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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An Exploration of Dialog Act Classification in Open-domain Conversational Agents and the Applicability of Text Data Augmentation
DownloadFall 2023
Recognizing dialog acts of users is an essential component in building successful conversational agents. In this work, we propose a dialog act (DA) classifier for two of our open domain conversational agents. For this, we curated a high-quality, multi-domain dataset with ∼24k user utterances...
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Fall 2023
Giving reasons for justifying the decisions made by classification models has received less attention in recent artificial intelligence breakthroughs than improving the accuracy of the models. Recently, AI researchers are paying more attention to filling this gap, leading to the introduction of...
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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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Fall 2022
Overfitting is a phenomenon when a machine learning system learns the patterns in training data so well that it starts to inauspiciously affect the model performance on unseen data. In practice, machine learning systems that overfit are not deployable rather systems that generalize well and do...
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Fall 2022
The rise of Deep Learning (DL) and its assistance in learning complex feature representations significantly impacted Reinforcement Learning (RL). Deep Reinforcement Learning (DRL) made it possible to apply RL to complex real-world problems and even achieve human-level performance. One of these...
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Fall 2022
Topic modelling seeks to uncover the conceptual and thematic content of collections of documents. These topics can be used as features for document indexing and classification. However, topic models are increasingly important as tools of applied research. As we seek to develop agents capable of...
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Spring 2021
This thesis investigates the use of general value functions for detecting anomalous behavior in machines. Identifying abnormal behavior is critical for ensuring the safety and reliability of any machine or industrial process. When the cause of these anomalies is due to accumulated wear on...