Abstract
A purpose of the thesis is to present a novel method in analyzing, synthesizing and managing knowledge documents. In general, the methodologies that synthesize and management patents are almost using the key phrases as indices of knowledge documents. But the key phrases extracted from patents are meaningless to computers. Thus a novel methodology to analyze and manage knowledge documents based on ontology is developed in this thesis research. The methodology in this thesis enables computers to understand the knowledge documents in some degree via ontology instead of key phrases in this thesis. The methodology is divided into several steps. First, experts have to construct the specific domain ontology schema and put some training data to train the system. Then a learning method from natural language texts is adapted to infer the principal ontology of the knowledge documents. Therefore we use the fuzzy logic control (FLC) to infer the relationship between the knowledge documents and a suitable document cluster via ontology. Finally, we will evaluate the effectiveness of this methodology, and compare with knowledge document clustering based on key phrases.