Proceedings of the 8th International Conference on Intellectual ...

Harri Ketamo
conceptual structure and user taught conceptual structure. The idea behind <strong>the</strong> search is relatively
close to image recognition with neural networks where images are replaced by concept maps.
Figure 1: Generalized framework <strong>of</strong> teachable media agents
Forming <strong>the</strong> semantics is based on tags retrieved from single piece <strong>of</strong> content. The semantic starts
from empty set <strong>of</strong> concepts and relations and it starts to grow according to <strong>the</strong> tags in pieces <strong>of</strong>
content that are defined as starting point by <strong>the</strong> user. For example, if a YouTube video include tags
‘interface’, ‘fail’ and ‘usability’, <strong>the</strong> starting semantic looks like in figure 2. The assumption is that <strong>the</strong>
tags are related to each o<strong>the</strong>r, because <strong>the</strong>y represent <strong>the</strong> same phenomena or issue.
Figure 2: Semantics with piece <strong>of</strong> content that include tags ‘interface’, ‘fail’ and ‘usability’
If <strong>the</strong> next video is tagged by words ‘usability’ and ‘interface design’ <strong>the</strong> semantic grows by <strong>the</strong> tags
and <strong>the</strong>ir relations (figure 3). In this case, <strong>the</strong> strength <strong>of</strong> ‘usability – interface’ –relation gets a value <strong>of</strong>
2, because this relation can be found from both <strong>of</strong> <strong>the</strong> pieces <strong>of</strong> <strong>the</strong> content. In fact <strong>the</strong> strength <strong>of</strong> <strong>the</strong>
relation is one <strong>of</strong> <strong>the</strong> key factors behind <strong>the</strong> successful modeling.
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