This 1 paper introduces and evaluates MovieExplorer, an interactive exploration tool designed to use the data available in a traditional ratings-based recommender system to provide an interactive interface more suited to user exploration and fulfillment of short-term recommendation needs. A field deployment with 1,950 users showed that users found the tool useful for a variety of exploration and short-term recommendation tasks, even preferring it to existing interfaces for several tasks. Experimentation with several design features found that the actual user navigation algorithms were significant (user satisfaction was lower for algorithms with faked controls) and that offering positive and negative feedback options led to increased feedback and user retention.
|Original language||English (US)|
|Title of host publication||Proceedings of the 33rd Annual ACM Symposium on Applied Computing, SAC 2018|
|Publisher||Association for Computing Machinery|
|Number of pages||10|
|State||Published - Apr 9 2018|
|Event||33rd Annual ACM Symposium on Applied Computing, SAC 2018 - Pau, France|
Duration: Apr 9 2018 → Apr 13 2018
|Name||Proceedings of the ACM Symposium on Applied Computing|
|Other||33rd Annual ACM Symposium on Applied Computing, SAC 2018|
|Period||4/9/18 → 4/13/18|
Bibliographical noteFunding Information:
We would like to thank F. Maxwell Harper and Qian Zhao for their help with the implementation of the MovieExplorer system and algorithm. This material is based upon work supported by a National Science Foundation Graduate Research Fellowship under Grant No. 00039202.
© 2018 ACM.
- Information exploration tools
- Interactive recommendation