User perspectives on personalized account-based recommender systems

 

Session Description:
This research is focused on understanding user preferences for “my account”-based recommendations of library content. By interviewing users we have explored user attitudes about three areas of recommendation services; including 1) eliciting preferences for recommendation, 2) displaying recommendations, and 3) revising recommendations based on results. User interviews indicated a need for crafting recommender services in library settings with transparent functionality. Users requested that system designers make clear how recommendations are designed and provided. Further findings indicated a desire to use recommender systems to explore interdisciplinary research domains that have otherwise not been considered.

 

Posted in 2019 Contributed Paper.