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resulting low vale of knowledge sharing. This can
result people will not be able to share knowledge.
The value of knowledge transferability and
knowledge complexity can be put in fuzzy logic
system to explain in high, medium, or low levels.
There are some limitations in our prototype as
follow. In the process of finding transferability and
complexity value we implement sense set which is
extracted from the electronic lexical database
WordNet. By using WordNet, we can only define
ontology concept as a single word which mean it can
only be noun and cannot be adjective, verb, or
adverb. In transferability measurement process, we
only in this paper consider is-a relationship omitting
properties (i.e. object property and datatype
property), constraints, and concept relations e.g.
siblings. Nevertheless, we assess the new knowledge
complexity after finding its transferability
considered above mentioned ontology attributes.
7 CONCLUSIONS AND FUTURE
WORK
We have addressed knowledge complexity and
knowledge transferability as key variables for
knowledge sharing. We then proposed the ontology
based approach which measures ontology
complexity and transferability to correspond to
knowledge complexity and knowledge
transferability respectively. Experimental studies
were given taking Pizza domain and a prototype has
been developed for proof of concept.
For future work a key variable of trust especially
in form of competency trust and benevolence trust
will be incorporated to measure knowledge sharing
in business intelligent applications. Our approach
can be applied to other domains for example e-
commerce and health domains. Future work also
includes a better complexity measurement which
will incorporate depth of concepts i.e. properties
(object property and datatype property) and
constraints, and breadth of concepts i.e. concept
relations e.g. siblings. Comparative evaluation will
also be needed in future work in order to compare
result with other researches in areas of knowledge
sharing measurement and alike.
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