Artist Recommendation System Using Hybrid Method: A Novel Approach-Reference-Cited by-同舟云学术

Artist Recommendation System Using Hybrid Method: A Novel Approach

Published:2019 Issue: Volume: Page:527-542
ISSN:2194-5357
Container-title:Emerging Research in Computing, Information, Communication and Applications
language:
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Author:

Dhruv Ajay,Kamath Aastha,Powar Anuja,Gaikwad Karan

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-13-5953-8_44

Reference20 articles.

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2. Ekvall, N. (2012). Movie recommendation system based on clustered low-rank approximation. Master’s Thesis, Department of Mathematics, Linkoping University, Sweden.

3. Shakirova, E. (2017). Collaborative filtering for music recommender system. Presented at the IEEE Conference of Russian, Young Researchers in Electrical and Electronic Engineering (EIConRus), St. Petersburg, Russia. https://doi.org/10.1109/elconrus.2017.7910613 .

4. Javari, A., & Jalili, M. (2014). A probabilistic model to resolve diversity–accuracy challenge of recommendation systems. In: Knowledge and Information Systems, London (pp. 609–627). https://doi.org/10.1007/s10115-014-0779-2 .

5. Ge, M., & Persia, F. (2017). Research challenges in multimedia recommender systems. Presented at the IEEE 11th International Conference on Semantic Computing, San Diego, CA, USA. https://doi.org/10.1109/icsc.2017.31 .

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