Graffiti: node labeling in heterogeneous networks

Authors:
Ralitsa Angelova;Gjergji Kasneci;Fabian M. Suchanek;Gerhard Weikum
Affiliations:
Max-Planck Institute for Informatics, Saarbruecken, Germany;Max-Planck Institute for Informatics, Saarbruecken, Germany;Max-Planck Institute for Informatics, Saarbruecken, Germany;Max-Planck Institute for Informatics, Saarbruecken, Germany
Venue:
Proceedings of the 18th international conference on World wide web
Year:
2009

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Graffiti: graph-based classification in heterogeneous networks

World Wide Web

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Abstract

We introduce a multi-label classification model and algorithm for labeling heterogeneous networks, where nodes belong to different types and different types have different sets of classification labels. We present a graph-based approach which models the mutual influence between nodes in the network as a random walk. When viewing class labels as "colors", the random surfer is "spraying" different node types with different color palettes; hence the name Graffiti. We demonstrate the performance gains of our method by comparing it to three state-of-the-art techniques for graph-based classification.