Knowledge Graphs
Download as PDF
Course Description
Knowledge graphs have emerged as a compelling abstraction for organizing world's structured knowledge over the internet, capturing relationships among key entities of interest to enterprises, and a way to integrate information extracted from multiple data sources. Knowledge graphs have also started to play a central role in machine learning and natural language processing as a method to incorporate world knowledge, as a target knowledge representation for extracted knowledge, and for explaining what is being learned. This class is a graduate level research seminar and will include lectures on knowledge graph topics (e.g., data models, creation, inference, access) and invited lectures from prominent researchers and industry practitioners. The seminar emphasizes synthesis of AI, database systems and HCI in creating integrated intelligent systems centered around knowledge graphs.
Grading Basis
RSN - Satisfactory/No Credit
Min
1
Max
1
Course Repeatable for Degree Credit?
No
Course Component
Seminar
Enrollment Optional?
No
Does this course satisfy the University Language Requirement?
No
Programs
CS520
is a
completion requirement
for:
- (from the following course set: )
- (from the following course set: )