Event Recommendation in Social Networks with Linked Data Enablement

Yinuo Zhang, Hao Wu, Vikram Sorathia, Viktor K. Prasanna

2013

Abstract

In recent years, social networking services have gained phenomenal popularity. They allow us to explore the world and share our findings in a convenient way. Event is a critical component in social networks. A user can create, share or join different events in their social circle. In this paper, we investigate the problem of event recommendation. We propose recommendation methods based on the similarity of an event’s content and a user’s interests in terms of topics. Specifically, we use Latent Dirichlet Allocation (LDA) to generate a topic distribution over each event and user. We also consider friend relationship and attendance history to increase recommendation accuracy. Moreover, we enable linked data as our data sources to collect contextual information related to events and users, and build an enhanced profile for them. As reliable resource, linked data is used to find structured knowledge and linkages among different knowledge. Finally, we conduct comprehensive experiments on various datasets in both academic community and popular social networking service.

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Paper Citation


in Harvard Style

Zhang Y., Wu H., Sorathia V. and K. Prasanna V. (2013). Event Recommendation in Social Networks with Linked Data Enablement . In Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8565-60-0, pages 371-379. DOI: 10.5220/0004443903710379


in Bibtex Style

@conference{iceis13,
author={Yinuo Zhang and Hao Wu and Vikram Sorathia and Viktor K. Prasanna},
title={Event Recommendation in Social Networks with Linked Data Enablement},
booktitle={Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2013},
pages={371-379},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004443903710379},
isbn={978-989-8565-60-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Event Recommendation in Social Networks with Linked Data Enablement
SN - 978-989-8565-60-0
AU - Zhang Y.
AU - Wu H.
AU - Sorathia V.
AU - K. Prasanna V.
PY - 2013
SP - 371
EP - 379
DO - 10.5220/0004443903710379