Encyclopedia of Machine Learning and Data Mining

Living Edition
| Editors: Claude Sammut, Geoffrey I. Webb

Collective Classification

  • Galileo Namata
  • Prithviraj Sen
  • Mustafa Bilgic
  • Lise Getoor
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4899-7502-7_44-1



Many real-world classification problems can be best described as a set of objects interconnected via links to form a network structure. The links in the network denote relationships among the instances such that the class labels of the instances are often correlated. Thus, knowledge of the correct label for one instance improves our knowledge about the correct assignments to the other instances it connects to. The goal of collective classification is to jointly determine the correct label assignments of all the objects in the network.

Motivation and Background

Traditionally, a major focus of machine learning is to solve classification problems: given a corpus of documents, classify each according to its topic label; given a collection of e-mails, determine which are spam; given a sentence, determine the part-of-speech tag for each word; given a handwritten document, determine the characters, etc. However, much of...


Class Label Link Prediction Unobserved Variable Inductive Logic Programming Local Classifier 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Galileo Namata
    • 1
  • Prithviraj Sen
    • 1
  • Mustafa Bilgic
    • 1
  • Lise Getoor
    • 1
  1. 1.University of MarylandCollege Park, MDUSA