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The Knowledge Seeker is a useful system to develop various
intelligent applications such as ontology-based search engine,
ontology-based text classification system, ontological agent
system, and semantic web system etc. The Knowledge Seeker contains
four different ontological components. First, it defines the
knowledge representation model !V Ontology Graph. Second, an
ontology learning process that based on chi-square statistics is
proposed for automatic learning an Ontology Graph from texts for
different domains. Third, it defines an ontology generation method
that transforms the learning outcome to the Ontology Graph format
for machine processing and also can be visualized for human
validation. Fourth, it defines different ontological operations
(such as similarity measurement and text classification) that can
be carried out with the use of generated Ontology Graphs. The final
goal of the KnowledgeSeeker system framework is that it can improve
the traditional information system with higher efficiency. In
particular, it can increase the accuracy of a text classification
system, and also enhance the search intelligence in a search
engine. This can be done by enhancing the system with machine
processable ontology.
The Knowledge Seeker is a useful system to develop various
intelligent applications such as ontology-based search engine,
ontology-based text classification system, ontological agent
system, and semantic web system etc. The Knowledge Seeker contains
four different ontological components. First, it defines the
knowledge representation model !V Ontology Graph. Second, an
ontology learning process that based on chi-square statistics is
proposed for automatic learning an Ontology Graph from texts for
different domains. Third, it defines an ontology generation method
that transforms the learning outcome to the Ontology Graph format
for machine processing and also can be visualized for human
validation. Fourth, it defines different ontological operations
(such as similarity measurement and text classification) that can
be carried out with the use of generated Ontology Graphs. The final
goal of the KnowledgeSeeker system framework is that it can improve
the traditional information system with higher efficiency. In
particular, it can increase the accuracy of a text classification
system, and also enhance the search intelligence in a search
engine. This can be done by enhancing the system with machine
processable ontology.
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