Cited By
View all- Zhao KLiu YYuan QChen LChen ZCong G(2016)Towards personalized mapsProceedings of the VLDB Endowment10.14778/3007263.30073059:13(1545-1548)Online publication date: 1-Sep-2016
SmartVenues: Recommending Popular and Personalised Venues in a City
Authors: 
Romain Deveaud, M-Dyaa Albakour, Jarana Manotumruksa, Craig Macdonald, Iadh OunisAuthors Info & Claims
Romain Deveaud, M-Dyaa Albakour, Jarana Manotumruksa, Craig Macdonald, Iadh OunisAuthors Info & ClaimsPages 2078 - 2080
Abstract
We present SmartVenues, a system that recommends nearby venues to a user who visits or lives in a city. SmartVenues models the variation over time of each venue's level of attendance, and uses state-of-the-art time series forecasting algorithms to predict the future attendance of these venues. We use the predicted levels of attendance to infer the popularity of a venue at future points in time, and to provide the user with recommendations at different times of the day. If the users log in with their Facebook account, the recommendations are personalised using the pages they "like". In this demonstrator, we detail the architecture of the system and the data that we collect in real-time to be able to perform the predictions. We also present two different interfaces that build upon our system to display the recommendations: a web-based application and a mobile application.
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R. Deveaud, M.-D. Albakour, C. Macdonald, and I. Ounis. Challenges in Recommending Venues within Smart Cities. In Proc. of i-ASC at ECIR, 2014.
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Index Terms
- SmartVenues: Recommending Popular and Personalised Venues in a City
Recommendations
Experiments with a Venue-Centric Model for Personalisedand Time-Aware Venue Suggestion
CIKM '15: Proceedings of the 24th ACM International on Conference on Information and Knowledge ManagementLocation-based social networks (LBSNs), such as Foursquare, fostered the emergence of new tasks such as recommending venues a user might wish to visit. In the literature, recommending venues has typically been addressed using user-centric recommendation ...
Personality and location-based social networks
We investigate personality and use of location based social networks.We examine the five-factor personality model against places that users check-in at.Conscientiousness positively correlates with the number of venues visited.Openness positively ...
Birds of a feather locate together? Foursquare checkins and personality homophily
In this paper we consider whether people with similar personality traits have a preference for common locations. Due to the difficulty in tracking and categorising the places that individuals choose to visit, this is largely unexplored. However, the ...
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Information & Contributors
Information
Published In
November 2014
2152 pages
ISBN:9781450325981
DOI:10.1145/2661829
- General Chairs:
- Jianzhong Li,
- X. Sean Wang,
- Program Chairs:
- Minos Garofalakis,
- Ian Soboroff,
- Torsten Suel,
- Min Wang
Copyright © 2014 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Published: 03 November 2014
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CIKM '14: 2014 ACM Conference on Information and Knowledge Management
November 3 - 7, 2014
Shanghai, China
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CIKM '14 Paper Acceptance Rate 175 of 838 submissions, 21%;
Overall Acceptance Rate 1,861 of 8,427 submissions, 22%
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Cited By
View all- Zhao KLiu YYuan QChen LChen ZCong G(2016)Towards personalized mapsProceedings of the VLDB Endowment10.14778/3007263.30073059:13(1545-1548)Online publication date: 1-Sep-2016
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