Hey Alexa, What Should I Read? Comparing the Use of Social and Algorithmic Recommendations for Different Reading Genres-Reference-Cited by-同舟云学术

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Hey Alexa, What Should I Read? Comparing the Use of Social and Algorithmic Recommendations for Different Reading Genres

Published:2021 Issue: Volume: Page:346-363
ISSN:0302-9743
Container-title:Diversity, Divergence, Dialogue
language:
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Author:

Zhang Huiwen,Buchanan George,McKay Dana

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-71292-1_27

Reference48 articles.

1. Tewari, A.S., Kumar, A., Barman, A.G.: Book recommendation system based on combine features of content based filtering, collaborative filtering and association rule mining. In: 2014 IEEE International Advance Computing Conference (IACC), pp. 500–503. IEEE (2014)

2. Rosa, R.L., Rodriguez, D.Z., Bressan, G.: Music recommendation system based on user’s sentiments extracted from social networks. IEEE Trans. Consum. Electron. 61, 359–367 (2015)

3. Subramaniyaswamy, V., Logesh, R., Chandrashekhar, M., Challa, A., Vijayakumar, V.: A personalised movie recommendation system based on collaborative filtering. Int. J. High Perform. Comput. Netw. 10, 54–63 (2017)

4. Kenthapadi, K., Le, B., Venkataraman, G.: Personalized job recommendation system at linkedin: practical challenges and lessons learned. In: Proceedings of the Eleventh ACM Conference on Recommender Systems, pp. 346–347. Association for Computing Machinery (2017)

5. Park, D.H., Kim, H.K., Choi, I.Y., Kim, J.K.: A literature review and classification of recommender systems research. Expert Syst. Appl. 39, 10059–10072 (2012)

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