In general an ontology is created by following a top-down, or so called genus-species approach, where the species are differentiated from the genus and from each other by means of differentiae [8]. The superconcept is the genus, every subconcept is a species, and the differentiae correspond to roles. To complete it a user organizes data into a proper structure, accompanied with the instances in that domain in order to complete the construction of an ontology. It is a concept learning procedure in a school, for example. Students first learn the general knowledge and apply it to their exercise and homework for practice. After they are more familiar with the knowledge, they can use what they have learned to solve the problems in their daily life. The deductive learning approach is based on the fundamental knowledge that a student has acquired already.
By contrast, a more intuitive way of learning is the bottom-up approach, which is based on atomism. That is also a frequently used way for humans to acquire knowledge. From sensing the world by vision, hearing, and touching, people learn information about actual objects, i.e., instances, in the world. After an instance has been collected, a relationship between it and existing knowledge will be created and an ontology will be formed automatically.
The primary goal of this thesis is to make a better instance input interface for the ontology development tool Protégé to simplify the procedure of ontology construction. The second goal is to show the feasibility of a bottom-up approach for the building of an ontology. Without setting up the organization of classes and properties (slots) first, a user simply inputs all the information from an instance and the program will form an ontology automatically. It means after an instance has been entered, the system will find a proper location inside of the ontology to store it.
| Identifer | oai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-1069 |
| Date | 01 April 2009 |
| Creators | Wei, Charles C.H. |
| Publisher | DigitalCommons@CalPoly |
| Source Sets | California Polytechnic State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Master's Theses |
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