Case-Based Reasoning in a Travel Medicine Application - Computational Intelligence in Healthcare: Advanced Methodologies - page 187

techniques and the application of the product line concept (known from soft-
ware engineering) creating knowledge lines. Furthermore this concept describes
the collaboration of distributed knowledge sources which makes this approach
adequate for an application scenario like docQuery. The system will follow the
CoMES-architecture, called SEASALT (Sharing Experience using an Agent-
based System Architecture LayouT), as it can be seen in Figure 3 and is ex-
plained in detail in Reichle et. al.[10].
The SEASALT architecture provides an application-independent architecture
that features knowledge acquisition from a web-community, knowledge mod-
ularization, and agent-based knowledge maintenance. It consists of five main
components which will be presented in the remaining of this section.
The SEASALT architecture is especially suited for the acquisition, handling
and provision of experiential knowledge as it is provided by communities of prac-
tice and represented within Web 2.0 platforms [11]. The Knowledge Provision
in SEASALT is based on the Knowledge Formalization that has been extracted
from WWW Knowledge Sources . Knowledge Sources can be wikis, blogs or web
forums in which users, in case of docQuery travel medicine experts, provide dif-
ferent kinds of information. They can for instance discuss topics in web forums
which are broadly established WWW communication medium and provide a
low entry barrier even to only occasional WWW users. Enabling an analysis of
the discussed topics, we enhanced the forum with agents for different purposes.
Additionally its contents can be easily accessed using the underlying data base.
The forum itself might serve as a communication and collaboration platform
for the travel medicine community, which consists of professionals such as scien-
tists and physicians who specialize in travel medicine and local experts from the
health sector and private persons such as frequent travelers and globetrotters.
The community uses the platform for sharing experiences, asking questions and
general networking. The forum is enhanced with agents that offer content-based
services such as the identification of experts, similar discussion topics, etc. and
communicate by posting relevant links directly into the respective threads [12].
The community platform is monitored by a second type of agents, the so
called Collector Agents. These agents are individually assigned to a specific Topic
Agent, their task is to collect all contributions that are relevant with regard to
their assigned Topic Agent's topic. The Collector Agents pass these contributions
on to the Knowledge Engineer and can in return receive feedback on the delivered
contribution's relevance. Our Collector Agents use information extraction tools,
like GATE [13] or TextMarker [14] to judge the relevance of a contribution. The
Knowledge Engineer reviews each Collector Agent's collected contributions and
realizes his or her feedback by directly adjusting the agents' rule base.
The SEASALT architecture is also able to include external knowledge sources
by equipping individual Collector agents with data base or web service protocols
or HTML crawling capabilities. This allows us to include additional knowledge
sources such as the web pages of the Department of Foreign Affairs or the WHO.
In order for the collected knowledge to be easily usable within the Knowl-
edge Line the collected contributions have to be formalized from their textual