Deep learning in recommender systems

Speaker:  Georgia Koutrika – Athens, Greece
Topic(s):  Information Systems, Search, Information Retrieval, Database Systems, Data Mining, Data Science

Abstract

Deep learning methods have dramatically improved the state-of-the-art in computer vision, speech recognition, natural language processing (NLP) and many other domains. Deep learning started to become popular in recommender systems very recently. Notable application areas include music, video, news and session-based recommendations. In this talk, I will give an overview of different types of neural networks, including Convolutional Neural Networks, Recurrent Neural Networks, Deep Neural Networks, (DNNs), and Auto Encoders (AE). Then, I will present examples of how different kinds of neural networks are applied in recommender systems including industrial-scale settings for video, music, and application recommendations.

About this Lecture

Number of Slides:  60 - 100
Duration:  60 - 90 minutes
Languages Available:  English, Greek
Last Updated: 

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