Knowledge-Based Recommender Systems

  • Charu C. Aggarwal
Chapter
First Online:

Abstract

Both content-based and collaborative systems require a significant amount of data about past buying and rating experiences. For example, collaborative systems require a reasonably well populated ratings matrix to make future recommendations. In cases where the amount of available data is limited, the recommendations are either poor, or they lack full coverage over the entire spectrum of user-item combinations.

Keywords

Recommender System User Requirement Customer Requirement Conjoint Analysis Similarity Metrics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Charu C. Aggarwal
    • 1
  1. 1.IBM T.J. Watson Research CenterYorktown HeightsUSA

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