Collective classification refers to the combined classification of a set of interlinked objects using all three types of information described above. Note that, ...

Sep 6, 2008 · We introduce four of the most widely used inference algorithms for classifying networked data and empirically compare them on both synthetic and real-world ...

We introduce four of the most widely used inference algorithms for classifying networked data and empirically compare them on both synthetic and real‐world ...

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

This type of joint reasoning about label correlations in network data is often referred to as collective classification. Classic machine learning literature ...

Collective classification (CC) utilizes network structure and un- derlying network properties such as label correlation to improve prediction accuracy. This ...

Sep 1, 2008 · We introduce four of the most widely used inference algorithms for classifying networked data and empirically compare them on both synthetic and real-world ...

Oct 22, 2024 · Internet traffic classification into specific network applications is essential for managing network resources and from security point of view.

In network theory, collective classification is the simultaneous prediction of the labels for multiple objects