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URN: urn:nbn:de:swb:90-485022

Context Selection on Attributed Graphs for Outlier and Community Detection

Iglesias Sánchez, Patricia

Abstract:
Today's applications store large amounts of complex data that combine information of different types. Attributed graphs are an example for such a complex database where each object is characterized by its relationships to other objects and its individual properties. Specifically, each node in an attributed graph may be characterized by a large number of attributes. In this thesis, we present different approaches for mining such high dimensional attributed graphs.


Zugehörige Institution(en) am KIT Institut für Programmstrukturen und Datenorganisation (IPD)
Publikationstyp Hochschulschrift
Jahr 2015
Sprache Englisch
Identifikator KITopen-ID: 1000048502
Verlag Karlsruhe
Abschlussart Dissertation
Fakultät Fakultät für Informatik (INFORMATIK)
Institut Institut für Programmstrukturen und Datenorganisation (IPD)
Prüfungsdaten 11.05.2015
Referent/Betreuer Prof. K. Böhm
Schlagworte data mining, attributed graphs, high dimensional, homophily, outliers, community detection
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