Mining recommendations from the web

ABSTRACT

In this paper we study the challenges and evaluate the effectiveness of data collected from the web for recommendations. We provide experimental results, including a user study, showing that our methods produce good recommendations in realistic applications. We propose a new evaluation metric, that takes into account the difficulty of prediction. We show that the new metric aligns well with the results from a user study.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.m Miscellaneous

General Terms:
Algorithms

Keywords:
evaluation metrics, recommender systems, web mining