Shlomo Berkovsky
ABSTRACT
The quantity of accessible information has been growing rapidly and far exceeded human processing capabilities. The sheer abundance of information often prevents users from discovering the desired information, or aggravates making informed and correct choices. This highlights the pressing need for intelligent personalized applications that simplify information access and discovery by taking into account users' preferences and needs. One type of personalized application that has recently become tremendously popular in research and industry is recommender systems. These provide to users personalized recommendations about information and products they may be interested to examine or purchase. Extensive research into recommender systems has yielded a variety of techniques, which have been published at a variety of conferences and adopted by numerous Web-sites. This tutorial will provide the participants with broad overview and thorough understanding of algorithms and practically deployed Web and mobile applications of personalized technologies.
Supplemental Material
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Index Terms
- Web Personalization and Recommender Systems
Recommendations
Recommender systems in e-commerce
EC '99: Proceedings of the 1st ACM conference on Electronic commerceThe Netflix Recommender System: Algorithms, Business Value, and Innovation
This article discusses the various algorithms that make up the Netflix recommender system, and describes its business purpose. We also describe the role of search and related algorithms, which for us turns into a recommendations problem as well. We ...
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