A case study on the application of the MAAEM methodology for the specification modeling of recommender systems in the legal domain

ICEIS 2007 - 9th International Conference on Enterprise Information Systems, Proceedings

Volumn SAIC, Issue , 2007, Pages 155-160

  Drumond, Lucas ^a   Girardi, Rosario ^a   Leite, Adriana ^a  

^a FEDERAL UNIVERSITY OF MARANHÃO   (Brazil)

Author keywords

Information filtering; Multi agent systems; Recommender systems; Semantic web

Indexed keywords

HIGH LEVEL OF ABSTRACTION; INFORMATION ACCESS; INFORMATION FILTERING; INFORMATION OVERLOADS; LEGAL DOMAINS; MULTI-AGENT; MULTI-AGENT APPLICATIONS; RECOMMENDER SYSTEMS; SOFTWARE DEVELOPMENT; SPECIFICATION MODELING;

INFORMATION SYSTEMS; SEMANTIC WEB; SEMANTICS; SOFTWARE AGENTS; SOFTWARE ENGINEERING;

MULTI AGENT SYSTEMS;

EID: 52549105914     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

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 Multi-agent Application Engineering. IX Workshop on Requirements Engineering, Cadernos do IME, UERI 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/EDBTPh.D. Workshop, 78-89.