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  5. Towards the Recommendation of Personalised Activity Sequences in the Tourism Domain
 
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Towards the Recommendation of Personalised Activity Sequences in the Tourism Domain

Author(s)
Kumar, Gunjan  
Jerbi, Houssem  
O'Mahony, Michael P.  
Uri
http://hdl.handle.net/10197/9190
Date Issued
2017-08-31
Date Available
2018-01-23T15:49:11Z
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 [16] 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
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
ACM
Subjects

Sequence recommendati...

Recommender systems

Activity recommendati...

Activity timeline mat...

Web versions
http://www.ec.tuwien.ac.at/rectour2017/
Language
English
Status of Item
Peer reviewed
Journal
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
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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insight_publication.pdf

Size

1.14 MB

Format

Adobe PDF

Checksum (MD5)

bbe20939af7c940505046108cba504d9

Owning collection
Insight Research Collection
Mapped collections
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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