A Survey on the Scalability of Recommender Systems for Social Networks-Reference-Cited by-同舟云学术

A Survey on the Scalability of Recommender Systems for Social Networks

Published:2018 Issue: Volume: Page:89-110
ISSN:
Container-title:Social Networks Science: Design, Implementation, Security, and Challenges
language:
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Author:

Sardianos C.,Tsirakis N.,Varlamis I.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-90059-9_5

Reference75 articles.

1. Symeonidis, P., Ntempos, D., & Manolopoulos, Y. (2014). Recommender systems for location-based social networks. Springer Science & Business Media.

2. Nepali, R., & Wang, Y. (2014). SocBridge: Bridging the gap between online social networks.

3. Chakradhar, S., & Raghunathan, A. (2010). IEEE: Best-effort computing: Re-thinking parallel software and hardware. In 2010 47th ACM/IEEE on Design Automation Conference (DAC) (pp. 865–870).

4. Ricci, F., Rokach, L., & Shapira, B. (2011). Introduction to recommender systems handbook (pp. 1–35). Springer.

5. Chen, H.-H., Ororbia, I., Alexander, G., & Giles, C. (2015). ExpertSeer: A Keyphrase Based Expert Recommender for Digital Libraries. arXiv:1511.02058 .

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