NFCS: An Efficient Neural Framework for Cold Start Recommendation
- 17 December 2021
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 395-397
Abstract
In this article we have illustrated an efficient and effective neural framework referred to as NFCS for cold start recommendation. In this neural network, the average ratings will be as the input, and the missing ratings will be regarded as the dropout rate for the neural network. Therefore, in the output layer ratings will be reconstructed, which could provide an high performance solution for cold start problem. Experimental results also demonstrate that NFCS could outperform state-of-the-art PMF and IRCD-ICS over real life datasets.Keywords
Funding Information
- Xihua University program (Z202115)
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