Towards the Recommendation of Personalised Activity Sequences in the Tourism Domain
|Title:||Towards the Recommendation of Personalised Activity Sequences in the Tourism Domain||Authors:||Kumar, Gunjan
O'Mahony, Michael P.
|Permanent link:||http://hdl.handle.net/10197/9190||Date:||31-Aug-2017||Abstract:||In this paper we consider the problem of recommending sequencesof activities to a user. The proposed approach leverages the order aswell as the context associated with the users past activity patternsto make recommendations. This work extends the general activityrecommendation framework proposed in  to iteratively recommendthe next sequence of activities to perform. We demonstratethe efficacy of our recommendation framework by applying it to thetourism domain and evaluations are performed using a real-world(checkin) dataset||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||ACM||Keywords:||Sequence recommendation; Recommender systems; Activity recommendation; Activity timeline matching||Language:||en||Status of Item:||Peer reviewed||Is part of:||Proceedings of the 2nd Workshop on Recommenders in Tourism co-located with 11th ACM Conference on Recommender Systems (RecSys 2017)||Conference Details:||RecTour 2017 2nd Workshop on Recommenders in Tourism. Como, Italy, 27 August 2017|
|Appears in Collections:||Computer Science Research Collection|
Insight Research Collection
Show full item record
This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.