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Find a path to becoming a Graph Modeling. Learn more at:
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Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Graph Modeling.
Provides a comprehensive overview of graph theory, covering both theoretical and practical aspects. It is written for students and researchers in computer science, as well as for practitioners who need to use graph theory in their work.
Provides a comprehensive overview of graph theory, covering both theoretical and practical aspects. It is written for students and researchers in computer science, as well as for practitioners who need to use graph theory in their work.
Provides a comprehensive overview of graph algorithms, covering both theoretical and practical aspects. It is written for students and researchers in computer science, as well as for practitioners who need to use graph algorithms in their work.
Provides a comprehensive overview of social network analysis, covering both theory and methods. It is written for students and researchers in the social sciences, as well as for practitioners who need to use social network analysis in their work.
Provides a review of the field of network science, covering topics such as network structure, dynamics, and applications. It is written for students and researchers in a variety of fields, including computer science, physics, and biology.
This book, written in Korean, provides a comprehensive overview of pattern recognition and machine learning, covering both theoretical and practical aspects. It is written for students and researchers in computer science, as well as for practitioners who need to use pattern recognition and machine learning in their work.
Provides an introduction to complex networks, covering topics such as network structure, dynamics, and applications. It is written for students and researchers in a variety of fields, including computer science, physics, and biology.
Provides a comprehensive overview of graph databases, covering their key concepts, data models, and query languages. It is written for developers who are new to graph databases or who want to learn more about how to use them.
Focuses on the data modeling aspects of graph databases. It covers different data modeling techniques and how to choose the right technique for a given application.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/f0b61e/graph
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