Social Recommendations: A historical perspective and recent advancements

Speaker:  Irwin King – Hong Kong, Hong Kong
Topic(s):  Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing

Abstract

With the exponential growth of information generated on the Internet, social recommendation has been a hot research topic in social computing after the popularization of social media as filtered suggestions (news, music, web pages, tags, etc.) are highly desirable to cope with the information explosion problem.  In this presentation, I plan to take a walk down memory lane by presenting some of the  seminal and pioneering work in social and location recommendation based on the matrix factorization framework. I will outline novel ways to use social ensemble, trust relations, tags, click-through rate, etc. to improve social and location recommender systems for a wide range of applications and services.  This talk will also elucidate some recent works that suggest potential future directions in social recommendations.

About this Lecture

Number of Slides:  60
Duration:  45 minutes
Languages Available:  English
Last Updated: 

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