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22. P. Lops, M. Gemmis, G. Semeraro,
Content-Based Recommender Systems: State of the Art and
Trends
, Chapter 3 (Springer, New York, 2011), pp. 73-105
23. R. Polikar, Ensemble based systems in decision making. Circuits Syst. Mag. IEEE
6
(3), 21-45
(2006)
24. S.J. Russell, P. Norvig,
Artificial Intelligence: A Modern Approach
, 2nd edn. (Pearson Educa-
tion, Upper Saddle River, 2003)
25. G. Smith, P. Ledbrook,
Grails in Action
, 1st edn. (Manning Publications, 2009). ISBN: 978-
193398893
26. D.E. Sullivan, B. Smyth, D. Wilson, Preserving recommender accuracy and diversity in sparse
datasets. Int. J. Artif. Intel. Tools
13
(01), 219-235 (2004)
27. N. Sundaresan, Recommender systems at the long tail, in
Proceedings of the Fifth ACM Con-
ference on Recommender Systems, RecSys'11
(ACM, New York, 2011), pp. 1-6
28. The Internet Movie Database Team. IMDb press room, about imdb. web resource, August
2014. Available online at
http://www.imdb.com/pressroom/about/
retrieved on 15th July 2014
29. A. Tizghadam, A. Leon-Garcia, Betweenness centrality and resistance distance in communi-
cation networks. IEEE Netw.
24
(6), 10-16 (2010)
30. Y. Zhao, G. Karypis, Evaluation of hierarchical clustering algorithms for document datasets,
in
Proceedings of the eleventh International Conference on Information and Knowledge Man-
agement, CIKM'02
(ACM, New York, 2002), pp. 515-524
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