articleMay 17, 2004Closed access

Shilling recommender systems for fun and profit

University of Minnesota

Indexed incrossref

Abstract

Recommender systems have emerged in the past several years as an effective way to help people cope with the problem of information overload. One application in which they have become particularly common is in e-commerce, where recommendation of items can often help a customer find what she is interested in and, therefore can help drive sales. Unscrupulous producers in the never-ending quest for market penetration may find it profitable to shill recommender systems by lying to the systems in order to have their products recommended more often than those of their competitors. This paper explores four open questions that may affect the effectiveness of such shilling attacks: which recommender algorithm is being…

Citation impact

643
total citations
FWCI
71.03
Percentile
100%
References
27
Citations per year

Authors

2

Topics & keywords

Keywords
  • Recommender system
  • Information overload
  • Competitor analysis
  • Computer science
  • Profit (economics)
  • Order (exchange)
  • World Wide Web
  • Business
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