\begin{thebibliography}{1}

\bibitem{lin2010semi}
Frank Lin and William~W Cohen.
\newblock Semi-supervised classification of network data using very few labels.
\newblock In {\em Advances in Social Networks Analysis and Mining (ASONAM),
  2010 International Conference on}, pages 192--199. IEEE, 2010.

\bibitem{subramanya2014graph}
Amarnag Subramanya and Partha~Pratim Talukdar.
\newblock Graph-based semi-supervised learning.
\newblock {\em Synthesis Lectures on Artificial Intelligence and Machine
  Learning}, 8(4):1--125, 2014.

\bibitem{talukdar2010experiments}
Partha~Pratim Talukdar and Fernando Pereira.
\newblock Experiments in graph-based semi-supervised learning methods for
  class-instance acquisition.
\newblock In {\em Proceedings of the 48th annual meeting of the association for
  computational linguistics}, pages 1473--1481. Association for Computational
  Linguistics, 2010.

\bibitem{zhou2004learning}
Denny Zhou, Olivier Bousquet, Thomas~N Lal, Jason Weston, and Bernhard
  Sch{\"o}lkopf.
\newblock Learning with local and global consistency.
\newblock In {\em Advances in neural information processing systems}, pages
  321--328, 2004.

\bibitem{zhu2003semi}
Xiaojin Zhu, Zoubin Ghahramani, and John~D Lafferty.
\newblock Semi-supervised learning using gaussian fields and harmonic
  functions.
\newblock In {\em Proceedings of the 20th International conference on Machine
  learning (ICML-03)}, pages 912--919, 2003.

\bibitem{zhu2009introduction}
Xiaojin Zhu and Andrew~B Goldberg.
\newblock Introduction to semi-supervised learning.
\newblock {\em Synthesis lectures on artificial intelligence and machine
  learning}, 3(1):1--130, 2009.

\end{thebibliography}
