Analyzing Tagged Resources for Social Interests Detection

Manel Mezghani, André Péninou, Corinne Amel Zayani, Ikram Amous, Florence Sèdes

Abstract

The social user is characterized by his social activity like sharing information, making relationships, etc. With the evolution of social content, the user needs more accurate information that reflects his interests. We focus on analyzing user's interests which are key elements for improving adaptation (recommendation, personalization, etc.). In this article, we are interested to overcome issues that influence the quality of adaptation in social networks, such as the accuracy of user's interests. The originality of our approach is the proposal of a new technique of user's interests detection by analyzing the accuracy of the tagging behaviour of the users in order to figure out the tags which really reflect the resources content. We focus on semi-structured data (resources), since they provide more comprehensible information. Our approach has been tested and evaluated in Delicious social database. A comparison between our approach and classical tag-based approach shows that our approach performs better.

References

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Paper Citation


in Harvard Style

Mezghani M., Péninou A., Zayani C., Amous I. and Sèdes F. (2014). Analyzing Tagged Resources for Social Interests Detection . In Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-027-7, pages 340-345. DOI: 10.5220/0004971303400345


in Bibtex Style

@conference{iceis14,
author={Manel Mezghani and André Péninou and Corinne Amel Zayani and Ikram Amous and Florence Sèdes},
title={Analyzing Tagged Resources for Social Interests Detection},
booktitle={Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2014},
pages={340-345},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004971303400345},
isbn={978-989-758-027-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Analyzing Tagged Resources for Social Interests Detection
SN - 978-989-758-027-7
AU - Mezghani M.
AU - Péninou A.
AU - Zayani C.
AU - Amous I.
AU - Sèdes F.
PY - 2014
SP - 340
EP - 345
DO - 10.5220/0004971303400345