Activity-Partner Recommendation

Abstract. In many activities, such as watching movies or having dinner, people prefer to find partners before participation. Therefore, when recommending activity items (e.g., movie tickets) to users, it makes sense to also recommend suitable activity partners. This way, (i) the users save time for finding activity partners, (ii) the effectiveness of the item recommendation is increased (users may prefer activity items more if they can find suitable activity partners), (iii) recommender systems become more interesting and enkindle users’ social enthusiasm. In this paper, we identify the usefulness of suggesting activity partners together with items in recommender systems. In addition, we propose and compare several methods for activity-partner recommendation. Our study includes experiments that test the practical value of activity-partner recommendation and evaluate the effectiveness of all suggested methods as well as some alternative strategies.

• Type: Journal
• Year: 2015
• Where: PAKDD
• Authors: Wenting Tu, David Wai-Lok Cheung, Nikos Mamoulis, Min Yang, Ziyu Lu
• Keywords: Data Mining, PAKDD 2015