Efficient and Scalable Job Recommender System Using Collaborative Filtering-Reference-Cited by-同舟云学术

Efficient and Scalable Job Recommender System Using Collaborative Filtering

Published:2020 Issue: Volume: Page:842-856
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
Short-container-title:

Author:

Mishra Ravita,Rathi Sheetal

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-1420-3_91

Reference33 articles.

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2. Yangi Z, Wui B, Zhengi K, Wang X, Lei L (2016) A survey of collaborative filtering-based recommender systems for mobile internet applications. https://doi.org/10.1109/access.2016.2573314

3. Kumar B, Sharma N (2016) Approaches, issues and challenges in recommender systems: a systematic review. Indian J Sci Technol 9(47). https://doi.org/10.17485/ijst/2015/v8i1/94892

4. Eirinaki M, Gao J, Varlamis I, Tserpes K (2017) Recommender systems for large-scale social networks: a review of challenges and solutions. Elsevier B.V. http://dx.doi.org/10.1016/j.future.2017.09.0150167-739X

5. Sun L, Wang X, Wang Z, Zhao H, Zhu W (2017) Social aware video recommendation for online social groups. IEEE Trans Multimed 19(3)

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