Matrix factorization techniques for recommender systems
In this thesis we study two basic matrix factorization techniques used in recommender systems, namely batch and stochastic gradient descent. Furthermore, data from Epinions.com, consisting of 40163 users and 139738 items is studied and statistically analyzed into its characteristic classes (i.e. use...
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| Main Authors: | , |
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| Other Authors: | |
| Language: | en_US |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://hdl.handle.net/11610/18038 |
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