[MapR Talk] Completely Real-time Recommendations

Document created by aalvarez Employee on Dec 1, 2015Last modified by aalvarez Employee on Dec 7, 2015
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Overview

In an effort to help grow organic communities interested in new technologies, MapR speakers around the world provide technical talks on numerous topics. Please browse our MapR Talks Directory  to learn how to search and request a talk in seconds.

 

Abstract

Currently deployed recommendation technology almost always provides real-time recommendations based on a model that is developed using off-line techniques. The use of off-line training severely limits the ability to deal with fast changing content such as news or auctions.

 

I will describe techniques which make it possible to move this training load into true real-time without loss of accuracy. Real-time training of recommendations is rarely done, partly because existing algorithms require periodic off-line training to correct accumulating inaccuracies. The techniques that I will describe do not require off-line training of any kind.

 

In addition, the techniques described in this talk are easy to implement using stream processing, noSQL databases and search engines.

 

KEYWORDS: Machine Learning, Data Science, Recommendations, NoSQL.

 

Location Availability & Request Link

North America. Please refer to the MapR Talks Directory  for specific countries.

You can request this talk here: Speaker Request

 

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