A CASE STUDY ON THE APPLICATION OF THE MAAEM METHODOLOGY FOR THE SPECIFICATION MODELING OF RECOMMENDER SYSTEMS IN THE LEGAL DOMAIN

Lucas Drumond, Rosario Girardi, Adriana Leite

2007

Abstract

Recommender systems have been target of continuous research over the last years, being used as an approach to the information overload problem. The Semantic Web is a new generation of the Web which aims at improving the effectiveness of information access on the Web by structuring its content in a machine readable way. Agents have been also object of active research on the software engineering field considering the high level of abstraction for software development provided by the multi-agent paradigm. This paper describes the modeling of Infonorma, a multi-agent recommender system for the legal domain developed under the guidelines of MAAEM, a methodology for multi-agent application development, which is also evaluated here.

References

  1. Adomavicius, G., Tuzhilin, A., 2005. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Trans. Knowledge and Data Engineering, v. 17, n. 6, 734- 749.
  2. Antoniou G., Van Harmelen, F., 2004. A Semantic Web Primer, MIT Press.
  3. Balabanovic, M., Shoham, Y., 1997. Fab: Content-Based, Collaborative Recommendation Comm. ACM, v. 40, n. 3, 66-72.
  4. Benjamins, V. R., Casanovas, P., Breuker, J., Gangemi, A., 2005. Law and the Semantic Web, an Introduction. In Lecture Notes in Computer Science, v. 3369, 1-17.
  5. Drumond L., Girardi. R., Lindoso, A., Marinho, L., 2006. A Semantic Web Based Recommender System for the Legal Domain. In Proc. of the European Conference on Artificial Intelligence (ECAI 2006) Workshop on Recommender Systems, Riva del Garda, Italy, pp. 81-83.
  6. Girardi. R., Marinho, L., 2007. A Domain Model of Web Recommender Systems based on Usage Mining and Collaborative Filtering, Requirements Engineering Journal, London, Springer-Verlag Press, v. 12, n. 1, pp. 23-40.
  7. Gruber, T., 1995. Toward Principles for the Design of Ontologies used for Knowledge Sharing. International Journal of Human-Computer Studies, n. 43, 907-928.
  8. Jennings, N., 2000. On Agent-based Software Engineering. Artificial Intelligence, v. 117, n. 2, 277- 296.
  9. Lindoso, A., Girardi, R., 2006. The SRAMO Technique for Analysis and Reuse of Requirements in Multiagent Application Engineering. IX Workshop on Requirements Engineering, Cadernos do IME, UERJ Press, v. 20, 41-50. Rio de Janeiro.
  10. McBride, B., 2002. Jena: a Semantic Web Toolkit. Internet Computing IEEE, 6, pp. 55-59.
  11. Middleton, S., Shadbolt, N., De Roure, D., 2004. Ontological User Profiling in Recommender Systems. ACM Transactions on Information Systems, 22, 54-88.
  12. Sebastiani, F., 2002. Machine learning in automated text categorization. ACM Computing Surveys.
  13. Sheth, B., Maes, P., 1993. Evolving Agents for Personalized Information Filtering. In Proc. Ninth IEEE Conf. Artificial Intelligence for Applications, 345-352.
  14. Tiscornia, D., 2001. Ontology-Driven Access to Legal Information. DEXA 12th International Workshop on Database and Expert Systems Applications, p. 792.
  15. Valente, A., 1995. Legal Knowledge Engineering: a Modeling Approach. IOS Press, Amsterdam, The Netherlands.
  16. Ziegler, C., 2004, Semantic Web Recommender Systems. Proc. Joint ICDE/EDBT Ph.D. Workshop, 78-89.
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Paper Citation


in Harvard Style

Drumond L., Girardi R. and Leite A. (2007). A CASE STUDY ON THE APPLICATION OF THE MAAEM METHODOLOGY FOR THE SPECIFICATION MODELING OF RECOMMENDER SYSTEMS IN THE LEGAL DOMAIN . In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 4: ICEIS, ISBN 978-972-8865-91-7, pages 155-160. DOI: 10.5220/0002389201550160


in Bibtex Style

@conference{iceis07,
author={Lucas Drumond and Rosario Girardi and Adriana Leite},
title={A CASE STUDY ON THE APPLICATION OF THE MAAEM METHODOLOGY FOR THE SPECIFICATION MODELING OF RECOMMENDER SYSTEMS IN THE LEGAL DOMAIN},
booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 4: ICEIS,},
year={2007},
pages={155-160},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002389201550160},
isbn={978-972-8865-91-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 4: ICEIS,
TI - A CASE STUDY ON THE APPLICATION OF THE MAAEM METHODOLOGY FOR THE SPECIFICATION MODELING OF RECOMMENDER SYSTEMS IN THE LEGAL DOMAIN
SN - 978-972-8865-91-7
AU - Drumond L.
AU - Girardi R.
AU - Leite A.
PY - 2007
SP - 155
EP - 160
DO - 10.5220/0002389201550160