ANALYSIS AND DESIGN OF A RECOMMENDER SYSTEM WITH AGENTS
Javier Portillo-Rodríguez, Aurora Vizcaino, Juan Pablo Soto, Mario Piattini
2009
Abstract
The aim of this paper is to provide a guideline for novel multi-agent systems developers in order to assist them in the development of this kind of systems. Papers frequently focus on describing how systems work, but seldom describe the different steps carried out to attain the final product. We shall attempt to show how the usage of a methodology facilitates the analysis, design and implementation phases, along with how the INGENIAS methodology has helped us to systematically construct a recommender system.
References
- Pavón, J. and J. Gómez-Sanz (2006). INGENIAS web site. http://grasia.fdi.ucm.es/ingenias/.
- Portillo, J., J. P. Soto, et al. (2008). A Model to Rate Trust in Communities of Practice. International Conference on Enterprise Information Systems (ICEIS 2008), Barcelona, Spain.
Paper Citation
in Harvard Style
Portillo-Rodríguez J., Vizcaino A., Soto J. and Piattini M. (2009). ANALYSIS AND DESIGN OF A RECOMMENDER SYSTEM WITH AGENTS . In Proceedings of the 4th International Conference on Software and Data Technologies - Volume 2: ICSOFT, ISBN 978-989-674-010-8, pages 175-178. DOI: 10.5220/0002253801750178
in Bibtex Style
@conference{icsoft09,
author={Javier Portillo-Rodríguez and Aurora Vizcaino and Juan Pablo Soto and Mario Piattini},
title={ANALYSIS AND DESIGN OF A RECOMMENDER SYSTEM WITH AGENTS},
booktitle={Proceedings of the 4th International Conference on Software and Data Technologies - Volume 2: ICSOFT,},
year={2009},
pages={175-178},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002253801750178},
isbn={978-989-674-010-8},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 4th International Conference on Software and Data Technologies - Volume 2: ICSOFT,
TI - ANALYSIS AND DESIGN OF A RECOMMENDER SYSTEM WITH AGENTS
SN - 978-989-674-010-8
AU - Portillo-Rodríguez J.
AU - Vizcaino A.
AU - Soto J.
AU - Piattini M.
PY - 2009
SP - 175
EP - 178
DO - 10.5220/0002253801750178