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Shallow Neural Models for Top-N Recommendation
Alfonso Landin, Daniel Valcarce, Javier Parapar, Álvaro Barreiro
2911 - 2912
10.3233/FAIA200449
Research Article
Frontiers in Artificial Intelligence and Applications
Volume 325: ECAI 2020
Abstract

In the field of Information Retrieval, word embedding models have shown to be effective in several tasks. In this paper, we show how one of these neural embedding techniques can be adapted to the recommendation task. This adaptation only makes use of collaborative filtering information, and the results show that it is able to produce effective recommendations efficiently.

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