Social Networks and Questions of Big Data. Graph search for communities with corresponding keywords


Seminararbeit, 2017

5 Seiten, Note: 1.3


Inhaltsangabe oder Einleitung

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.

Details

Titel
Social Networks and Questions of Big Data. Graph search for communities with corresponding keywords
Hochschule
Ludwig-Maximilians-Universität München  (Institut für Informatik)
Veranstaltung
Recent Developments in Data Science
Note
1.3
Autor
Jahr
2017
Seiten
5
Katalognummer
V369515
ISBN (eBook)
9783668471757
Dateigröße
572 KB
Sprache
Englisch
Schlagworte
community, graph, network, search, mining, social network, data, informatics
Arbeit zitieren
Andrea Attwenger (Autor:in), 2017, Social Networks and Questions of Big Data. Graph search for communities with corresponding keywords, München, GRIN Verlag, https://www.grin.com/document/369515

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