Displaying User Profiles to Elicit User Awareness in Recommender Systems

When users understand their preferences and interests, they may find it easier to make a decision to buy an item new to them. Such understanding may also help users explore new categories because it enables them to judge differences from their current preferences or interests. In our research, we show users their user profiles created by a recommender system and ask them whether they learn any new knowledge about their preferences or interests. Because user profiles are usually implicitly created by machine learning techniques based on the users' usual activities such as browsing and shopping, they might include user preferences or interests of which the users are not explicitly aware. We conduct a user experiment to know whether the users can aware new knowledge about their interests or preferences. We also analyze the content of those discoveries.