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2018 | OriginalPaper | Chapter

Improved Personalized Rankings Using Implicit Feedback

Authors : Josef Feigl, Martin Bogdan

Published in: Artificial Neural Networks and Machine Learning – ICANN 2018

Publisher: Springer International Publishing

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Abstract

Most users give feedback through a mixture of implicit and explicit information when interacting with websites. Recommender systems should use both sources of information to improve personalized recommendations. In this paper, it is shown how to integrate implicit feedback information in form of pairwise item rankings into a neural network model to improve personalized item recommendations. The proposed two-sided approach allows the model to be trained even for users where no explicit feedback is available. This is especially useful to alleviate a form of the new user cold-start problem. The experiments indicate an improved predictive performance especially for the task of personalized ranking.

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Literature
1.
Bennett, J., Lanning, S., Netflix, N.: The Netflix Prize. In: KDD Cup and Workshop in Conjunction with KDD (2007)
2.
Bishop, C.M.: Pattern Recognition and Machine Learning (Information Science and Statistics). Springer, New York Inc., Heidelberg, New York (2006)MATH
3.
Bradley, A.P.: The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recogn. 30(7), 1145–1159 (1997)CrossRef
4.
Feigl, J., Bogdan, M.: Collaborative filtering with neural networks. In: ESANN 2017, 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, pp. 441–446 (2017)
5.
Feigl, J., Bogdan, M.: Neural networks for implicit feedback datasets. In: ESANN 2018, 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, pp. 255–260 (2018)
6.
Harper, F.M., Konstan, J.A.: The movielens datasets: history and context. ACM Trans. Interact. Intell. Syst. 5(4), 19:1–19:19 (2015)CrossRef
7.
Hu, Y., Koren, Y., Volinsky, C.: Collaborative filtering for implicit feedback datasets. In: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining, ICDM 2008, pp. 263–272 (2008)
8.
Kingma, D.P., Ba, J.: ADAM: a method for stochastic optimization. CoRR abs/1412.6980 (2014)
9.
Klambauer, G., Unterthiner, T., Mayr, A., Hochreiter, S.: Self-normalizing neural networks. CoRR abs/1706.02515 (2017)
10.
Koren, Y., Bell, R., Volinsky, C.: Matrix factorization techniques for recommender systems. Computer 42(8), 30–37 (2009)CrossRef
11.
Krogh, A., Hertz, J.A.: A simple weight decay can improve generalization. In: Advances in Neural Information Processing Systems, vol. 4, pp. 950–957. Morgan Kaufmann (1992)
12.
13.
Rendle, S.: Factorization machines with LIBFM. ACM Trans. Intell. Syst. Technol. 3(3), 57:1–57:22 (2012)CrossRef
14.
Rendle, S., Freudenthaler, C., Gantner, Z., Schmidt-Thieme, L.: BPR: Bayesian personalized ranking from implicit feedback. In: Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, UAI 2009, pp. 452–461. AUAI Press, Arlington (2009)
15.
Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Neurocomputing: foundations of research. In: Learning Representations by Back-propagating Errors, pp. 696–699. MIT Press, Cambridge (1988)
16.
17.
Takács, G., Pilászy, I., Németh, B., Tikk, D.: Scalable collaborative filtering approaches for large recommender systems. J. Mach. Learn. Res. 10, 623–656 (2009)
Metadata
Title
Improved Personalized Rankings Using Implicit Feedback
Authors
Josef Feigl
Martin Bogdan
Copyright Year
2018
Book
Artificial Neural Networks and Machine Learning – ICANN 2018

Print ISBN: 978-3-030-01417-9

Electronic ISBN: 978-3-030-01418-6

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-01418-6_37

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