Collaborative filtering and deep learning based recommendation system for cold start items

Abstract

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Highlights • Two recommendation models were proposed for cold start items. • The models combine time-aware collaborative filtering and deep learning. • Experiment on Netflix dataset showed large improvement over existing approaches.

A performance comparison of two emotion-recognition implementations using OpenCV and Cognitive Services API

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Efficient Tensor Strategy for Recommendation

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