News Recommendation in Real-Time - Smart Information Systems: Computational Intelligence for Real-Life Applications - page 176

36. L. Li, D.-D. Wang, S.-Z. Zhu, T. Li, Personalized news recommendation: a review and an
experimental investigation. J. Comput. Sci. Technol. 26 (5), 754-766 (2011)
37. L. Li, W. Chu, J. Langford, R.E. Schapire, A contextual-bandit approach to personalized news
article recommendation, in Proceedings of the 19th International Conference on World Wide
Web—WWW'10 (ACM Press, New York, 2010), p. 661
38. L. Li, W. Chu, J. Langford, X. Wang, Unbiased offline evaluation of contextual-bandit-based
news article recommendation algorithms, in Proceedings of the Fourth ACM International
Conference on Web Search and Data Mining—WSDM'11 (ACM Press, New York, 2011),
p. 297
39. B. Liu, Web Data Mining (Springer, New York, 2008)
40. J. Liu, P. Dolan, E. Rønby Pedersen. Personalized news recommendation based on click behav-
ior, in Proceedings of the International Conference on Intelligent User Interfaces , pp. 31-40
(2010)
41. N.N. Liu, Q. Yang, Eigenrank: a ranking-oriented approach to collaborative filtering, in SIGIR ,
pp. 83-90 (2008)
42. A. Lommatzsch, Real-time news recommendation using context-aware ensembles, in Advances
in Information Retrieval (Springer, New York, 2014), pp. 51-62
43. L. Lü, M. Medo, C.-H. Yeung, Y.-C. Zhang, Y.-K. Zhang, T. Zhou, Recommender systems.
Phys. Rep. 519 , 1-49 (2012)
44. Y. Lv, T. Moon, P. Kolari, Z. Zheng, X. Wang, Y. Chang, Learning to model relatedness for
news recommendation, in Proceedings of the 20th International Conference on World Wide
Web—WWW'11 , p. 57 (2011)
45. F. Maes, L. Wehenkel, D. Ernst, Learning to play k-armed bandit problems, in Proceedings of
the 4th International Conference on Agents and Artificial Intelligence ( ICAART 2012 ) (2012)
46. A. Montes-García, J.M.Á. Rodríguez, J.E. Labra-Gayo, M. Martínez-Merino, Towards a
journalist-based news recommendation system: the Wesomender approach. Expert Syst. Appl.
40 (17), 6735-6741 (2013)
47. O. Phelan, K. Mccarthy, M. Bennett, B. Smyth, Terms of a feather: content-based news dis-
covery and recommendation using twitter, in ECIR , pp. 448-459 (2011)
48. P. Pu, L. Chen, Trust-inspiring explanation interfaces for recommender systems. Knowl.-Based
Syst. 20 (6), 542-556 (2007)
49. Y. Ren, G. Li, W. Zhou, Learning user preference patterns for top-n recommendations, in
2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent
Technology , pp. 137-144 (2012)
50. S. Rendle. Learning recommender systems with adaptive regularization, in WSDM , pp. 133-
142 (2012)
51. S. Rendle, C. Freudenthaler, Improving pairwise learning for item recommendation from
implicit feedback, in Proceedings of the 7th ACM International Conference on Web Search
and Data Mining—WSDM'14 , pp. 273-282 (2014)
52. F. Ricci, L. Rokach, B. Shapira, P.B. Kantor, Recommender Systems Handbook (Springer, New
York, 2011)
53. R. Salakhutdinov, A. Mnih, G. Hinton, Restricted boltzmann machines for collaborative fil-
tering, in Proceedings of the 24th International Conference on Machine Learning—ICML'07
(ACM Press, New York, 2007), pp. 791-798
54. M. Seeger, Scalable collaborative bayesian preference learning, in AISTATS , vol. 33 (2014)
55. G. Shani, A. Gunawardana, Evaluating recommendation systems, in Recommender Systems
Handbook (Springer, New York, 2011)
56. Y. Shi, A. Karatzoglou, L. Baltrunas, M. Larson, N. Oliver, A. Hanjalic, CLiMF: learning
to maximize reciprocal rank with collaborative less-is-more filtering, in RecSys , pp. 139-146
(2012)
57. J.-W. Son, A.-Y. Kim, S.-B. Park, A location-based news article recommendation with explicit
localized semantic analysis, in SIGIR , pp. 293-302 (2013)
58. G. Takacs, I. Pilaszy, B. Nemeth, D. Tikk, Scalable collaborative filtering approaches for large
recommender systems. J. Mach. Learn. Res. 10 , 623-656 (2009)