We use a network structure index to select nodes for labeling, and we show that this approach substantially outperforms random selection and selection based on ...

Abstract: Active inference seeks to maximize classification performance while minimizing the amount of data that must be labeled ex ante.

It is shown that efficient methods for indexing network structure can be exploited to select high-value nodes for labeling, and this approach substantially ...

Active inference seeks to maximize classification perfor- mance while minimizing the amount of data that must be labeled ex ante. This task is particularly ...

Exploiting Network Structure for Active Inference in Collective Classification. Resume Mining of Communities in Social Network · A Divisive Hierarchical ...

Labeling nodes in a network is an important problem that has seen a growing interest. A number of methods that exploit both local and relational information ...

A number of methods that exploit both local and relational information have been developed for this task. Acquiring the labels for a few nodes at inference time ...

... Exploiting network structure for active inference in collective classification. In: Proceedings of the Seventh. IEEE International Conference on Data Mining ...

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This article introduces four of the most widely used inference algorithms for classifying networked data and empirically compare them on both synthetic and ...