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Spring 2023
There has been a renewed interest in commonsense as a stepping stone toward achieving human-level intelligence. By digesting enormous amounts of data in different forms, such as visual, lingual, and sensory, humans are able to create a world model for themselves. It is hypothesized that this...
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Constructing Knowledge Graphs with Language Models and Learning Hierarchies from Graphs using Probabilistic Topic Modeling
DownloadFall 2024
Knowledge graphs leverage a data model structured as a graph or topology to represent and manipulate data. Knowledge graphs, abbreviated as KGs, consist of interconnected factual statements, conceptualized as distinct entities referred to as the {\em subject} and {\em object}, linked by a...
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Spring 2017
Edge-labeled graphs are widely used to describe relationships between entities in a database. We study a class of queries on edge-labeled graphs, referred to as exemplar queries, where each query gives an example of what the user is searching for. Given an exemplar query, we study the problem of...
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Spring 2024
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...