• Corpus ID: 118721868

An Evaluation Framework for Interactive Recommender System

  title={An Evaluation Framework for Interactive Recommender System},
  author={Oznur Kirmemis Alkan and Elizabeth M. Daly and Adi Botea},
Traditional recommender systems present a relatively static list of recommendations to a user where the feedback is typically limited to an accept/reject or a rating model. However, these simple modes of feedback may only provide limited insights as to why a user likes or dislikes an item and what aspects of the item the user has considered. Interactive recommender systems present an opportunity to engage the user in the process by allowing them to interact with the recommendations, provide… 

Figures from this paper



User Control in Recommender Systems: Overview and Interaction Challenges

This paper reviews and classify the different approaches from the research literature of putting the users into active control of what is recommended, highlights the challenges related to the design of the corresponding user interaction mechanisms and presents the results of a survey-based study.

A Short Introduction to Learning to Rank

  • Hang Li
  • Computer Science
    IEICE Trans. Inf. Syst.
  • 2011
Several learning to rank methods using SVM techniques are described in details and the fundamental problems, existing approaches, and future work of learning toRank are explained.