NetKit-SRL: A Network Learning Toolkit and its use for Classification of Networked Data

  • Sofus Macskassy
  • Foster Provost

This paper describes NetKit-SRL, or NetKit for short, a toolkit for learning from and classifying networked data.  The toolkit is open-source and publicly available.  It is modular and built for ease of plug-and-play—such that it is easy to add new modules and have them interact with other existing modules.  Currently available NetKit modules are focused on “batch” within-network learning and classification: given a partially labeled network, where all nodes and edges are already known to exist, estimate the class membership probability of the unlabeled nodes in the network.  NetKit has been used in various network domains such as websites, citation graphs, movies and social networks.

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