Open AccessModel of Recommendation System for for Indexing and Retrieving the Learning Object based on Multiagent System
Author(s) -
Ronaldo Lima Rocha Campos,
Rafaela Lunardi Comarella,
Rosemary Silva da Silveira
Publication year - 2012
Publication title -
respuestas
Language(s) - English
Resource type - Journals
eISSN - 2422-5053
pISSN - 0122-820X
DOI - 10.22463/0122820x.422
Subject(s) - computer science , search engine indexing , metadata , learning object , object (grammar) , information retrieval , mechanism (biology) , domain (mathematical analysis) , recommender system , artificial intelligence , world wide web , mathematical analysis , philosophy , mathematics , epistemology
This paper proposes a multiagent system application model for indexing, retrieving and recommendation learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata standards. The searching mechanism covers several different learning object repositories and the same object can be described in these repositories by the use of different types of fields. Aiming to improve accuracy and coverage in terms of recovering a learning object and improve the signification of the results we propose an information retrieval model based on the multiagent system approach and an ontological model to describe the knowledge domain covered.Keywords: AI in education, multi-agent systems, learning objects, recommendation systems.