MODEL-BASED COLLABORATIVE FILTERING FOR TEAM BUILDING SUPPORT

Miguel Veloso, Alípio Jorge, Paulo J. Azevedo

Abstract

In this paper we describe an application of recommender systems to team building in a company or organization. The recommender system uses a collaborative filtering model based approach. Recommender models are sets of association rules extracted from the activity log of employees assigned to projects or tasks. Recommendation is performed at two levels: first by recommending a single team element given a partially built team; and second by recommending changes to a completed team. The methodology is applied to a case study with real data. The results are evaluated through experimental tests and one survey to potential users.

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Paper Citation


in Harvard Style

Veloso M., Jorge A. and J. Azevedo P. (2004). MODEL-BASED COLLABORATIVE FILTERING FOR TEAM BUILDING SUPPORT . In Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 972-8865-00-7, pages 241-248. DOI: 10.5220/0002636502410248


in Bibtex Style

@conference{iceis04,
author={Miguel Veloso and Alípio Jorge and Paulo J. Azevedo},
title={MODEL-BASED COLLABORATIVE FILTERING FOR TEAM BUILDING SUPPORT},
booktitle={Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2004},
pages={241-248},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002636502410248},
isbn={972-8865-00-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - MODEL-BASED COLLABORATIVE FILTERING FOR TEAM BUILDING SUPPORT
SN - 972-8865-00-7
AU - Veloso M.
AU - Jorge A.
AU - J. Azevedo P.
PY - 2004
SP - 241
EP - 248
DO - 10.5220/0002636502410248