Authors:
Roberval Mariano
;
Rosario Girardi
;
Adriana Leite
;
Lucas Drumond
and
Djefferson Maranhão
Affiliation:
Federal University of Maranhão, Brazil
Keyword(s):
Recommender Systems, Semantic Web, Information Filtering, Domain Engineering, Multi-agent Systems.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Cloud Computing
;
Data Engineering
;
Engineering Information System
;
Enterprise Information Systems
;
Information Retrieval
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Pattern Recognition
;
Requirements Analysis And Management
;
Semantic Web Technologies
;
Services Science
;
Software Agents and Internet Computing
;
Software Engineering
;
Symbolic Systems
Abstract:
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.