On Unexpectedness in Recommender Systems: Or How to Expect the Unexpected

@inproceedings{Adamopoulos2011OnUI,
  title={On Unexpectedness in Recommender Systems: Or How to Expect the Unexpected},
  author={Panagiotis Adamopoulos and Alexander Tuzhilin},
  booktitle={DiveRS@RecSys},
  year={2011}
}
Although the broad social and business success of recommender systems has been achieved across several domains, there is still a long way to go in terms of user satisfaction. One of the key dimensions for improvement is the concept of unexpectedness. In this paper, we propose a model to improve user satisfaction by generating unexpected recommendations based on the utility theory of economics. In particular, we propose a new concept of unexpectedness as recommending to users those items that… CONTINUE READING
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References

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Showing 1-10 of 27 references

Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques

IEEE Transactions on Knowledge and Data Engineering • 2012
View 2 Excerpts

Evaluating Recommendation Systems

Recommender Systems Handbook • 2011
View 1 Excerpt

Introducing Serendipity in a Content-Based Recommender System

2008 Eighth International Conference on Hybrid Intelligent Systems • 2008
View 1 Excerpt