Semantic Movie Recommendations - Smart Information Systems: Computational Intelligence for Real-Life Applications - page 144

by K. Aberer, K.-S. Choi, N. Noy, D. Allemang, K.-I. Lee, L. Nixon, J. Golbeck, P. Mika,
D. Maynard, R. Mizoguchi, G. Schreiber, P. Cudré-Mauroux (Springer, Berlin, 2007), pp.
722-735
3. D. Beckett, B. McBride, RDF/XML syntax specification (revised). Technical report. World
Wide Web Consortium ( W3C ) (2004)
4. D. Beckett, T. Berners-Lee, E. Prud'hommeaux, Terse RDF triple language. Technical report.
World Wide Web Consortium ( W3C ) (2011)
5. C.M. Bishop, Pattern Recognition and Machine Learning ( Information Science and Statistics )
(Springer, New York, 2006)
6. C. Bizer, T. Heath, K. Idehen, T. Berners-Lee, Linked data on the web (LDOW2008),
in Proceedings of the 17th International Conference on WWW (ACM, New York, 2008)
pp. 1265-1266
7. C. Bizer, J. Lehmann, G. Kobilarov, S. Auer, C. Becker, R. Cyganiak, S. Hellmann, DBpedia—
a crystallization point for the web of data. Web Seman. Sci. Serv. Agents World Wide Web
7 (3), 154-165 (2009). The Web of Data
8. K. Bollacker, C. Evans, P. Paritosh, T. Sturge, J. Taylor, Freebase: a collaboratively created
graph database for structuring human knowledge, in Proceedings of the 2008 ACM SIGMOD
International Conference on Management of Data, SIGMOD'08 (ACM, New York, 2008),
pp. 1247-1250
9. S. Bourke, K. McCarthy, B. Smyth, Power to the people: exploring neighbourhood formations
in social recommender system, in Proceedings of the 5th ACM Conference on Recommender
Systems, RecSys'11 (ACM, New York, 2011) pp. 337-340
10. Creative Commons Matt Lee. Creative commons Wiki. Web resource, 15th July 2014. http://
wiki.creativecommons.org/
11. M. Dean, G. Schreiber, OWL, web ontology language. W3C recommendation. World Wide
Web Consortium ( W3C ) (2004)
12. M. Fatemi, L. Tokarchuk, An empirical study on IMDb and its communities based on the
network of co-reviewers, in Proceedings of the First Workshop on Measurement, Privacy, and
Mobility, MPM'12 (ACM, New York, 2012) pp. 7:1-7:6
13. GroupLens Research.MovieLens data sets. Online resource, available at http://www.grouplens.
org/node/73, October 2006
14. T. Heath, C. Bizer, Semantic annotation and retrieval: web of data, in Handbook of Semantic
Web Technologies , ed. by J. Domingue, D. Fensel, J.A. Hendler (Springer, Berlin, 2011),
pp. 191-229
15. J. Herlocker, J. Konstan, A. Bochers, J. Riedl, An algorithmic framework for performing
collaborative filtering, in Proceedings of the 22nd International Conference on Research and
Development in Information Retrieval ( SIGIR'99 ) (1999)
16. J.L. Herlocker, J.A. Konstan, L.G. Terveen, J.T. Riedl, Evaluating collaborative filtering rec-
ommender systems. ACM Trans. Inf. Syst. (TOIS) 22 (1), 5-53 (2004)
17. Y. Koren, R. Bell, C. Volinsky, Matrix factorization techniques for recommender systems.
Computer 42 (8), 30-37 (2009)
18. J. Kunegis, A. Lommatzsch, Learning spectral graph transformations for link prediction, in
Proceedings of the 26th Annual International Conference on Machine Learning ICML'09
(ACM, New York, 2009), pp. 1-8
19. A. Lommatzsch, B. Kille, S. Albayrak, An agent-based movie recommender system combining
the results computed based on heterogeneous semantic datasets, in Proceedings of the 13th GI
International Conference on Innovative Internet Community Systems and the Workshop on
Autonomous Systems, I2CS'13 (VDI, Düsseldorf, 2013)
20. A. Lommatzsch, D. Ploch, E.W.D. Luca, S. Albayrak, Named entity disambiguation for German
news articles, in Proceedings of LWA2010 - Workshop-Woche: Lernen , ed. by M. Atzmüller,
D. Benz, A. Hotho, G. Stumme (Wissen and Adaptivität, Kassel 2010)
21. A. Lommatzsch, T. Plumbaum, S. Albayrak, A linked dataverse knows better: boosting rec-
ommendation quality using semantic knowledge, in Proceedings of the 5th International Con-
ference on Advances in Semantic Processing (IARIA, Wilmington, 2011), pp. 97-103