Complex approach of data with graphs and other tools

Monday 7 December 2015
by  Jean Pierre FERAL
popularity : 4%

- A way to represent and manage "big data" is to use a graph database. Such a database uses graph structures for semantic queries with nodes, edges and properties to represent and store data locally indexed.
- A graph database is essentially a collection of nodes and edges. Each node represents an entity (such as a person or business) and each edge represents a connection or relationship between two nodes.
Every node in a graph database is defined by a unique identifier, a set of outgoing edges and/or incoming edges and a set of properties expressed as key/value pairs.
Each edge is defined by a unique identifier, a starting-place and/or ending-place node and a set of properties.
- Graph databases are well-suited for analyzing interconnections, which is why there has been a lot of interest in using graph databases to mine data from different media. CIGESMED is testing them in a global ecology framework (graph transversal).

- More information here.

- In CIGESMED we will complement this approach by data mining in order to reveal new data patterns which are not accessible through classical approaches.

Presentations supporting the discussion (PPTX) and/or video

Complex approach with graphs and data visualization, interpretative and analysing tools, Romain David

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