LKT-FM: A Novel Rating Pattern Transfer Model for Improving Non-overlapping Cross-Domain Collaborative Filtering-Reference-Cited by-同舟云学术

LKT-FM: A Novel Rating Pattern Transfer Model for Improving Non-overlapping Cross-Domain Collaborative Filtering

Published:2017 Issue: Volume: Page:641-656
ISSN:0302-9743
Container-title:Machine Learning and Knowledge Discovery in Databases
language:
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Author:

Zang Yizhou,Hu Xiaohua

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-71246-8_39

Reference20 articles.

1. Fernndez-Tobas, I., Cantador, I., Kaminskas, M., Ricci, F.: Cross-domain recommender systems: a survey of the state of the Art. In: CERI, pp. 187–198 (2012)

2. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);S Berkovsky,2007

3. Tang, J., Wu, S., Sun, J., Su, H.: Cross-domain collaboration recommendation. In: KDD, pp. 1285–1293 (2012)

4. Ding, C.H.Q., Li, T., Peng, W., Park, H.: Orthogonal nonnegative matrix t-factorizations for clustering. In: KDD, pp. 126–135 (2006)

5. Li, B., Yang, Q., Xue, X.: Can movies and books collaborate? Cross-domain collaborative filtering for sparsity reduction. In: IJCAI, pp. 2052–2057 (2009)

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5. Design and Evaluation of Cross-Domain Recommender Systems;Recommender Systems Handbook;2012-02-24