Recommender Systems in E-Commerce Introduction ... - GroupLens
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Recommender Systems in E-Commerce Introduction ... - GroupLens
Recommender Systems in E-Commerce. Joseph A. Konstan. John Riedl.
University of Minnesota. {konstan,riedl}@cs.umn.edu http://www.cs.umn.edu/
Research/ ...
Recommender Systems in E-Commerce
ACM E-Commerce 2000
Introduction Recommender Systems in E-Commerce Joseph A. Konstan John Riedl University of Minnesota {konstan,riedl}@cs.umn.edu
What are Recommender Systems? Goals of this Tutorial Brief History of Recommender Systems
recommender systems and their application to E-commerce ◆ Know enough about recommender systems technology to evaluate application ideas ◆ Be able to design and critique recommender application designs ◆ See where recommender systems have been, and where they are going 2000 Joseph A. Konstan and John Riedl
ACM E-Commerce 2000
Outline Introduction ◆
History of recommenders
History of Recommender Systems
The Virtual Shopkeeper ◆
Recommenders for online selling
MovieLens Case Study Recommender Communities The Nine Principles Application Design Model and Exercise Conclusions, Privacy, and the Future 2000 Joseph A. Konstan and John Riedl
ACM E-Commerce 2000
2000 Joseph A. Konstan and John Riedl
The Early Years … Why cave dwellers survived
ACM E-Commerce 2000
Information Filtering Information retrieval ◆ Dynamic
How editors are like cave dwellers
◆ Static
information need content base
Information filtering
Critics, critics, everywhere
◆ Static
information need content base
◆ Dynamic
2000 Joseph A. Konstan and John Riedl
October 17, 2000
ACM E-Commerce 2000
2000 Joseph A. Konstan and John Riedl
ACM E-Commerce 2000
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Recommender Systems in E-Commerce
ACM E-Commerce 2000
Collaborative Filtering
Automated CF The GroupLens Project (CSCW ’94)
Premise ◆ Information
needs more complex than keywords or topics: quality and taste
◆ ACF
rate items are correlated with other users ➨ personal predictions for unrated items ➨ users
Small Community: Manual ◆ Tapestry
– database of content & comments ◆ Active CF – easy mechanisms for forwarding content to relevant readers
2000 Joseph A. Konstan and John Riedl
for Usenet News
➨ users
ACM E-Commerce 2000
◆ Nearest-Neighbor
Approach
➨ find
people with history of agreement ➨ assume stable tastes
2000 Joseph A. Konstan and John Riedl
ACM E-Commerce 2000
ACF Blossomed 1995 ◆ ◆
Ringo (later Firefly) Bellcore Video Recommender
1996 Recommender Systems Workshop Early commercialization Agents Inc. (later Firefly) Net Perceptions new issues of scale and performance! ◆
◆
2000 Joseph A. Konstan and John Riedl
ACM E-Commerce 2000
2000 Joseph A. Konstan and John Riedl
Today
Introductions
Broad research community ◆ live
research systems ◆ substantial integration with machine learning, information filtering
Increasing commercial application ◆ available
commercial tools
2000 Joseph A. Konstan and John Riedl
October 17, 2000
ACM E-Commerce 2000
ACM E-Commerce 2000
John Riedl Collaborative computing, multimedia Joe Konstan User interfaces, multimedia GroupLens Research Net Perceptions 2000 Joseph A. Konstan and John Riedl
ACM E-Commerce 2000
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Recommender Systems in E-Commerce
ACM E-Commerce 2000
The Virtual Shopkeeper
2000 Joseph A. Konstan and John Riedl
ACM E-Commerce 2000
The Consumer Is King
2000 Joseph A. Konstan and John Riedl
Carorder.com Screenshot with price information
2000 Joseph A. Konstan and John Riedl
ACM E-Commerce 2000
Book pricebot Screenshot with price information
2000 Joseph A. Konstan and John Riedl
October 17, 2000
ACM E-Commerce 2000
eBay Screenshot of mechanical clock detail page
Priceline.com Screenshot of hotel purchase with price information
