Combining Long-term and Discussion-generated Preferences in Group Recommendations
UMAP(2017)
摘要
In this abstract, we discuss how long-term and discussion-generated preferences can be appropriately combined in supporting group decision making. We measure the quality of a group recommendation model by varying the importance given to these two types of preferences in different group scenarios, where the group setting may impact on user's behavior. The results of a simulation experiment illustrate that when users' preferences are not influenced by the group, the preference aggregation model should weigh more the long-term preferences. In contrast, when discussion-generated preferences tend either to align with each other or to diverge due to the group setting, it is beneficial to take into account more the discussion-generated preferences, which help to capture the newly arising interests of the users.
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