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The Semantic Web is a vision to simplify and improve knowledge
reuse on the Web. It is all set to alter the way humans benefit
from the web from active interaction to somewhat passive
utilization through the proliferation of software agents and in
particular personal assistants that can better function and thrive
on the Semantic Web than the conventional web. Agents can parse,
understand and reason about information available on Semantic Web
pages in an attempt to use it to meet user's needs. Such personal
assistants will be driven by rules , axioms and the internal model
or profile that the agents have inside them for the user. An
intrinsic and important pre-requisite for a personal assistant or
rather any agent is to manipulate information available on the
Semantic Web in the form of ontologies, axioms, and rules written
in various semantic markup languages. We have developed a model
architecture for such a personal assistant dealing with real-world
semantic markup. The agent reasons with semantic markup written in
DAML+OIL, using the Java Expert System Shell (JESS) as the
reasoning engine. This software assistant views information
providers on the Semantic Web as recommender agents that have a
limited view of the user's preferences and provides a improved
notion of personalization by collaborating with peer personal
assistants (what are referred to as buddy agents) within
communities that the user has identified as trusted parties to
exchange information with. Collaboration is achieved through simple
solicitation and recommendation of information with these buddy
agents.
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