Engineering Research Seminar | Graph Queries in Network and Linked Data
Roberts Hall, Room 101
In a wide array of disciplines, data can be modeled as an interconnected network of entities, where various attributes are associated with both the entities and the relations among them, enabling us to apply the wealth of graph algorithms to query and manage the data. In this talk, we first look at a few compelling use cases for modeling physical and information networks as graphs and using graph analysis techniques to perform tasks such as network management, anomaly detection and analytics. Next, we look at the current landscape of graph storage and processing software available.
Graph databases are emerging as an important technology that can support faster graph query support compared to relational databases and scale more naturally to large data sets . Graph processing techniques include classical graph algorithms such as shortest path and reachability, which depend only on the structure of the network, as well as emerging queries that require both the topology and content information of the network data. Finally, we take a look some of the current approaches to visualize large graph data.
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