Abstract or Introduction
This essay deals with a graph search for communities with corresponding keywords.
The era of big data and world-spanning social networks has highlighted the necessity of ways to make sense of this vast amount of information. Data can be arranged in a graph of connected vertices, therefore giving it a basic structure. If the vertices are further described by keywords, the structure is called an attributed graph. This paper discusses a query algorithm that scans these attributed graphs for communities that are not only structurally linked - therefore forming subgraphs - but also share the same keywords. This method might give new insights into the composition of large networks, highlight interesting connections and give opportunities for effectively targeted marketing. As a specific use case, the idea of the attributed community query is applied to the example of a film recommendation program.
- Quote paper
- Andrea Attwenger (Author), 2017, Social Networks and Questions of Big Data. Graph search for communities with corresponding keywords, Munich, GRIN Verlag, https://www.grin.com/document/369515