The objective of this course is to provide students with a solid foundation in graph data management and mining. Students will learn how to model complex data using graph structures and understand the theoretical principles behind graph representation, traversal, and querying. The course also covers key data mining techniques on graphs, including frequent subgraph mining, community detection and centrality analysis.

This course covers the fundamentals of graph theory, graph data models and querying techniques. It includes topics such as graph traversal, graph similarity, frequent subgraph mining, community detection and centrality metrics. The course also introduces applications of graph mining in social network analysis, recommendation systems.