Balasubramanyan, R., Dalvi, B. B. & Cohen, W. W.
(2013).
From Topic Models to Semi-supervised Learning: Biasing Mixed-Membership Models to Exploit Topic-Indicative Features in Entity Clustering..
In H. Blockeel, K. Kersting, S. Nijssen & F. Zelezný (eds.),
ECML/PKDD (2) (p./pp. 628-642),
: Springer.
ISBN: 978-3-642-40990-5
Backstrom, L. & Leskovec, J.
(2011).
Supervised random walks: predicting and recommending links in social networks.
Proceedings of the fourth ACM international conference on Web search and data mining (p./pp. 635--644),
New York, NY, USA: ACM.
ISBN: 978-1-4503-0493-1
Backstrom, L. & Leskovec, J.
(2010).
Supervised Random Walks: Predicting and Recommending Links in Social Networks
(cite arxiv:1011.4071)
Ramage, D., Hall, D., Nallapati, R. & Manning, C. D.
(2009).
Labeled LDA: A Supervised Topic Model for Credit Attribution in Multi-labeled Corpora.
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1 (p./pp. 248--256),
Stroudsburg, PA, USA: Association for Computational Linguistics.
ISBN: 978-1-932432-59-6
Schmidt-Thieme, L.
(2005).
Compound Classification Models for Recommender Systems..
Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 27-30 November 2005 (p./pp. 378-385),
Houston, Texas, USA: IEEE Computer Society.
ISBN: 0-7695-2278-5
Zhu, X.
(2005).
Semi-Supervised Learning Literature Survey
(1530).
Computer Sciences, University of Wisconsin-Madison
.
Basu, S., Banerjee, A. & Mooney, R. J.
(2004).
Active Semi-Supervision for Pairwise Constrained Clustering. ,
, 333--344.