An ontology-based architecture for cooperative information agents
Frederico Freitas, Guilherme Bittencourt · 2003
In the Web, extractor agents process classes of pages (like 'call for papers ' pages, researchers' pages, etc), neglecting the relevant fact that some of them are interrelated forming clusters (e.g., science). We propose here an architecture for cognitive multi-agent systems to retrieve and classify pages from these clusters, based on data extraction. To enable cooperation, two design requirements are crucial: (a) a Web vision coupling a vision for contents (classes and attributes to be extracted) to a functional vision (the role of pages in information presentation); (b) explicit representation of agents ' knowledge and abilities in the form of ontologies, both about the cluster's domain and agents ' tasks. Employing this Web vision and agents' cooperation can accelerate the retrieval of useful pages. We got encouraging results with two agents for the page classes of scientific events and articles. A comparison of results to similar systems comes up with two requirements for such systems: functional categorization and a thoroughly detailed ontology of the cluster. 1