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On the Pros and Cons of Explanation-Based Ranking

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Case-Based Reasoning Research and Development (ICCBR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10339))

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Abstract

In our increasingly algorithmic world, it is becoming more important, even compulsory, to support automated decisions with authentic and meaningful explanations. We extend recent work on the use of explanations by recommender systems. We review how compelling explanations can be created from the opinions mined from user-generated reviews by identifying the pros and cons of items and how these explanations can be used for recommendation ranking. The main contribution of this work is to look at the relative importance of pros and cons during the ranking process. In particular, we find that the relative importance of pros and cons changes from domain to domain. In some domains pros dominate, in other domains, cons play a more important role. And in yet other domains there is a more equitable relationship between pros and cons. We demonstrate our findings on 3 large-scale, real-world datasets and describe how to take advantage of these relative differences between pros and cons for improved recommendation performance.

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Notes

  1. 1.

    http://www.darpa.mil/program/explainable-artificial-intelligence.

  2. 2.

    www.yelp.com/dataset_challenge.

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Acknowledgement

This research is supported by Science Foundation Ireland through the Insight Centre for Data Analytics under grant number SFI/12/RC/2289.

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Authors and Affiliations

  1. Insight Centre for Data Analytics, University College Dublin, Belfield, Dublin 4, Ireland

    Khalil Muhammad, Aonghus Lawlor & Barry Smyth

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  1. Khalil Muhammad
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  2. Aonghus Lawlor
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  3. Barry Smyth
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Correspondence to Khalil Muhammad .

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Editors and Affiliations

  1. Naval Research Laboratory, Navy Center for Applied Research in AI, Washington, District of Columbia, USA

    David W. Aha

  2. LORIA/Bâtiment B/équipe Orpailleur, University of Lorraine, Vandœuvre-lès-Nancy Cedex, France

    Jean Lieber

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Muhammad, K., Lawlor, A., Smyth, B. (2017). On the Pros and Cons of Explanation-Based Ranking. In: Aha, D., Lieber, J. (eds) Case-Based Reasoning Research and Development. ICCBR 2017. Lecture Notes in Computer Science(), vol 10339. Springer, Cham. https://doi.org/10.1007/978-3-319-61030-6_16

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  • DOI: https://doi.org/10.1007/978-3-319-61030-6_16

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-61030-6

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