Bibliographic Details
| Title: |
EventAware: A mobile recommender system for events. |
| Authors: |
Horowitz, Daniel1, Contreras, David1,2 dcontreras@maia.ub.es, Salamó, Maria1 |
| Source: |
Pattern Recognition Letters. Apr2018, Vol. 105, p121-134. 14p. |
| Subjects: |
Recommender systems, Existence theorems, User interfaces, Natural language processing, Machine learning |
| Abstract: |
Developing a recommender system for events raises several issues that are different from other domains. Events rapidly disappear, users’ preferences quickly change over time, and direct feedback does not exist for events that have not taken place. As the recommendations will not be further available, user’s context become a key factor for providing accurate recommendations. In this paper we introduce EventAware, a context-aware mobile recommender system to personalize the agenda of users attending to a congress. In particular, we first introduce the EventAware system, which includes an intuitive user interface with an attractive design to enhance user experience. EventAware incorporates some implicit contextual information, automatically initializes both the user’s profiles with minimal user interaction and the properties of the items and it uses a context-aware tag-based recommender algorithm. We demonstrate its usability through a live-user case-study in one of the biggest events of mobile technology in the world, held in Barcelona. [ABSTRACT FROM AUTHOR] |
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| Database: |
Engineering Source |