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Authors: Marie Françoise Canut 1 ; Manel Mezghani 2 ; Sirinya On-At 1 ; André Péninou 1 and Florence Sèdes 1

Affiliations: 1 University of Toulouse, France ; 2 University of Toulouse and Sfax University, France

ISBN: 978-989-758-097-0

Keyword(s): User’s Profile, User’s Interests, Tags, Social Network Analysis, Egocentric Network, Community.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Enterprise Information Systems ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Society, e-Business and e-Government ; Software Agents and Internet Computing ; Symbolic Systems ; User Profiling and Recommender Systems ; Web 2.0 and Social Networking Controls ; Web Information Systems and Technologies

Abstract: With the growing amount of social media contents, the user needs more accurate information that reflects his interests. We focus on deriving user’s profile and especially user’s interests, which are key elements to improve adaptive mechanisms in information systems (e.g. recommendation, customization). In this paper, we are interested in studying two approaches of user’s profile derivation from egocentric networks: individual-based approach and community-based approach. As these approaches have been previously applied in a co-author network and have shown their efficiency, we are interested in comparing them in the context of social annotations or tags. The motivation to use tagging information is that tags are proved relevant by many researches to describe user’s interests. The evaluation in Delicious social databases shows that the individual-based approach performs well when the semantic weight of user’s interests is taken more in consideration and the community-based approach perf orms better in the opposite case. We also take into consideration the dynamic of social tagging networks. To study the influence of time in the efficiency of the two user’s profile derivation approaches, we have applied a time-awareness method in our comparative study. The evaluation in Delicious demonstrates the importance of taking into account the dynamic of social tagging networks to improve effectiveness of the tag-based user profiling approaches. (More)

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Paper citation in several formats:
Françoise Canut, M.; Mezghani, M.; On-At, S.; Péninou, A. and Sèdes, F. (2015). A Comparative Study of Two Egocentric-based User Profiling Algorithms - Experiment in Delicious.In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-097-0, pages 632-639. DOI: 10.5220/0005377006320639

@conference{iceis15,
author={Marie Fran\c{C}oise Canut. and Manel Mezghani. and Sirinya On{-}At. and André Péninou. and Florence Sèdes.},
title={A Comparative Study of Two Egocentric-based User Profiling Algorithms - Experiment in Delicious},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2015},
pages={632-639},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005377006320639},
isbn={978-989-758-097-0},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - A Comparative Study of Two Egocentric-based User Profiling Algorithms - Experiment in Delicious
SN - 978-989-758-097-0
AU - Françoise Canut, M.
AU - Mezghani, M.
AU - On-At, S.
AU - Péninou, A.
AU - Sèdes, F.
PY - 2015
SP - 632
EP - 639
DO - 10.5220/0005377006320639

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