A case study on domain analysis of semantic Web multi-agent Recommender Systems

The huge amount of data available on the Web and its dynamic nature is the source of an increasing demand of information filtering applications such as recommender systems. The lack of semantic structure of Web data is a barrier for improving the effectiveness of this kind of applications. This paper introduces ONTOSERS-DM, a domain model that specifies the common and variable requirements of Recommender Systems based on the ontology technology of the Semantic Web, using three information filtering approaches: content-based, collaborative and hybrid filtering. ONTOSERS-DM was modeled under the guidelines of MADEM, a methodology for Multi-Agent Domain Engineering, using the ONTOMADEM tool.