research-article

Interacting with Recommenders—Overview and Research Directions

Authors:

Michael Jugovac,

Dietmar JannachAuthors Info & Claims

ACM Transactions on Interactive Intelligent Systems (TiiS), Volume 7, Issue 3

Article No.: 10, Pages 1 - 46

https://doi.org/10.1145/3001837

Published: 19 September 2017 Publication History

Abstract

Automated recommendations have become a ubiquitous part of today’s online user experience. These systems point us to additional items to purchase in online shops, they make suggestions to us on movies to watch, or recommend us people to connect with on social websites. In many of today’s applications, however, the only way for users to interact with the system is to inspect the recommended items. Often, no mechanisms are implemented for users to give the system feedback on the recommendations or to explicitly specify preferences, which can limit the potential overall value of the system for its users.

Academic research in recommender systems is largely focused on algorithmic approaches for item selection and ranking. Nonetheless, over the years a variety of proposals were made on how to design more interactive recommenders. This work provides a comprehensive overview on the existing literature on user interaction aspects in recommender systems. We cover existing approaches for preference elicitation and result presentation, as well as proposals that consider recommendation as an interactive process. Throughout the work, we furthermore discuss examples of real-world systems and outline possible directions for future works.

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ACM Transactions on Interactive Intelligent Systems Volume 7, Issue 3

September 2017

164 pages

ISSN:2160-6455

EISSN:2160-6463

DOI:10.1145/3143523

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Revised: 01 October 2016

Received: 01 March 2016

Published in TIIS Volume 7, Issue 3

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