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Fall 2022

Parniani,Mohammad Sahand

Graph-based Knowledge Bases (KBs) are composed of relational facts that can be perceived as two entities, called head and tail, linked through a relation. Processes of constructing KBs, i.e., populating them with such facts, as well as revising and updating them are of special importance. Such...

Fall 2023

Ogezi, Michael

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....

Fall 2023

Alexander, Graham

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...

Spring 2023

Strobl, Michael

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),...

Spring 2024

Costello, Jeremy

We introduce the background of the natural language processing field, outlining the benefits and drawbacks of rule-based versus statistical methods. We present knowledge graphs as a way to integrate the explainability of rule-based methods and the power of statistical methods, large language...

Spring 2023

Viggiato De Almeida, Markos

The gaming industry has experienced a sharp growth in recent years, surpassing other popular entertainment segments, such as the film industry. With the ever-increasing scale of the gaming industry and the fact that players are extremely difficult to satisfy, it has become extremely challenging...

Fall 2020

Luan, Yixing

Word sense disambiguation (WSD) is one of the core tasks in natural language processing and its objective is to identify the sense of a content word (nouns, verbs, adjectives, and adverbs) in context, given a predefined sense inventory. Although WSD is a monolingual task, it has been conjectured...

Fall 2017

Nicolai, Garrett J

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...

Spring 2016

Salameh, Mohammad K

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...

Spring 2021

Samuel, Hamman W

It has gotten increasingly harder for laypersons to determine the veracity of online health information. This is because of the explosion of content in health social media, allowing anyone with an Internet connection to create and propagate health-related content. This includes both innocuous and...