Graph Mining: Applications (invited talk)

Varování

Publikace nespadá pod Filozofickou fakultu, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.

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VACULÍK Karel

Rok publikování 2016
Druh Článek ve sborníku
Konference Proceedings in Informatics and Information Technologies. Bratislava: WIKT & DaZ
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
Obor Informatika
Klíčová slova graph mining; network analysis; data mining; classification; anomaly detection; community detection; recommendation
Popis Traditional data mining algorithms typically assume data instances to be independent. However, there is a lot of real-world scenarios where relationships between data instances exist and they are principal for data understanding. For example, there are relationships between people in social networks, between chemical elements in chemical compounds, etc. It is difficult or even impossible to express such information in the classical attribute-value representation. Graph mining is an area of data mining that uses a graph representation of data and it allows us to exploit the relationships in the data. The goal of this talk is to present diverse successful applications of graph mining on real-world graphs.
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