Architectural design of a multi-agent recommender system for the legal domain

Authors:
Lucas Drumond;Rosario Girardi;Adriana Leite
Affiliations:
Federal University of Maranhão, São Luís, Brazil;Federal University of Maranhão, São Luís, Brazil;Federal University of Maranhão, São Luís, Brazil
Venue:
Proceedings of the 11th international conference on Artificial intelligence and law
Year:
2007

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Abstract

Legal information sources are characterized by their growth and dynamism since new laws are written every day. Recommender systems are used as an approach to the information overload problem. Thus they can help professionals of the legal area to deal with legal information sources. This paper describes the architectural design of Infonorma, a multi-agent recommender system for the legal domain. Infonorma monitors a repository of legal normative instruments and classifies them into legal branches. Each user specifies his/her interests for certain legal branches and receives recommendations of instruments they might be interested in. The information source is entirely written according to Semantic Web standards. Infonorma was developed under the guidelines of MAAEM, a software development methodology for multi-agent application engineering.