An extension of the crisp ontology for uncertain information modeling-fuzzy ontology map

In the current World Wide Web (WWW), users find it difficult to locate relevant information using search engines. This may be due to the fact that the current World Wide Web lacks semantic markup. One of the possible solutions for this problem is Semantic Web. In the latest Semantic Web technology, descriptive markup languages, such as Resource Description Framework (RDF) and Web Ontology Language (OWL), were proposed to model the web content in a machine-readable way which assists information gathering and automatic searching by software agents. Since these ontology markup languages deal with 'hard' semantics with the description and manipulation of crisp data, they are not capable to represent uncertain information.; This thesis proposes an extension of the current ontology representation which supports uncertain information modeling. The extension is called Fuzzy Ontology Map (FOM) which is based on the integration of fuzzy theory and graph theory. By considering an ontology as a graph, an ontology graph can be constructed by using a vertex to represent a subject or literal value and an arrow to represent a predicate. Each edge in the ontology graph has a fuzzy membership value. A FOM is a connection matrix which collects the membership values between classes in the ontology graph. Thus, a fuzzy ontology could be created by using the FOM and the ontology document (RDF/OWL). This research also defines a set of algorithms for inferring fuzzy relationships in an FOM. It is possible to use an FOM to develop real-world applications and systems that can deal with imprecise or vague information. To demonstrate how FOM works, two prototype applications were developed, SemTour:HK and iJADE FreeWalker (iJFW). SemTour:HK is a tourist information portal integrating an ontology with the FOM to allow users to perform fuzzy searches. iJFW is an intelligent agent-based tourist guiding system which is used in mobile devices. It was developed based on the integration of intelligent agent technology (IAT) and Global Positioning System (GPS) with FOM.