Recommender systems in e-commerce

J. Ben Schafer, Joseph Konstan, John Riedl

Research output: Chapter in Book/Report/Conference proceedingConference contribution

988 Scopus citations

Abstract

Recommender systems are changing from novelties used by a few E-commerce sites, to serious business tools that are re-shaping the world of E-commerce. Many of the largest commerce Web sites are already using recommender systems to help their customers find products to purchase. A recommender system learns from a customer and recommends products that she will find most valuable from among the available products. In this paper we present an explanation of how recommender systems help Ecommerce sites increase sales, and analyze six sites that use recommender systems including several sites that use more than one recommender system. Based on the examples, we create a taxonomy of recommender systems, including the interfaces they present to customers, the technologies used to create the recommendations, and the inputs they need from customers. We conclude with ideas for new applications of recommender systems to E-commerce.

Original languageEnglish (US)
Title of host publicationProceedings of the 1st ACM Conference on Electronic Commerce, EC 1999
Pages158-166
Number of pages9
DOIs
StatePublished - Dec 1 1999
Event1st ACM Conference on Electronic Commerce, EC 1999 - Denver, CO, United States
Duration: Nov 3 1999Nov 5 1999

Publication series

NameACM International Conference Proceeding Series

Other

Other1st ACM Conference on Electronic Commerce, EC 1999
CountryUnited States
CityDenver, CO
Period11/3/9911/5/99

Keywords

  • cross-sell
  • customer loyalty
  • electronic commerce
  • interface
  • mass customization
  • recommender systems
  • up-sell

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