Date of Award
5-2020
Culminating Project Type
Starred Paper
Degree Name
Computer Science: M.S.
Department
Computer Science and Information Technology
College
School of Science and Engineering
First Advisor
Andrew Anda
Second Advisor
Bryant Julstrom
Third Advisor
Richard Sundheim
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Keywords and Subject Headings
Artificial Intelligence, Knowledge Graph, Knowledge Graph Embedding
Abstract
Knowledge graphs provide machines with structured knowledge of the world. Structured, machine-readable knowledge is necessary for a wide variety of artificial intelligence tasks such as search, translation, and recommender systems. These knowledge graphs can be embedded into a dense matrix representation for easier usage and storage. We first discuss knowledge graph components and knowledge base population to provide the necessary background knowledge. We then discuss popular methods of embedding knowledge graphs in chronological order. Lastly, we cover how knowledge graph embeddings improve both knowledge base population and a variety of artificial intelligence tasks.
Recommended Citation
Tschida, Catherine, "Knowledge Graphs and Knowledge Graph Embeddings" (2020). Culminating Projects in Computer Science and Information Technology. 32.
https://repository.stcloudstate.edu/csit_etds/32
