| dc.description.abstract | Research of relevant document discovery is practical and attractive to many
researchers, and there are different solutions to this issue. Some solutions have been
adopted in real world environments, such as electronic articles publishers. These
publishers offer different information search options such as keywords, full-text,
phrase, boolean expression…etc, for users to retrieve documents. Most relevant
document discovery techniques are originally from the domain of information
retrieval. The core concept of semantic web is ontology, which has been applied in
various domains, such as web service, agent communication, knowledge
management… etc. However, there was few paper applied ontology to the research of
relevant document discovery. Therefore, in this paper, ontology is applied to the issue
of relevant documents discovery and a prototype system is constructed to implement
the method proposed. With the input of a user selected document, the designed
prototype system could generate a number of closely related documents that originally
stored in the repository. The process of the prototype system could be mainly divided
into the following steps: (1) transforming the input text document into OWL format (2)
determining if the input document already exists in the ontology repository of the
system (3) if the input document does not exist in ontology repository, then the
program will calculate the similarity between the input ontology and the documents
originally stored in ontology repository, and retrieving related documents with higher
similarity values. Ontology extraction and similarity calculation are the cores that
applied the concept of ontology to the prototype system. The objective of ontology
extraction is to transform TXT format documents into OWL formats according to the
characteristics of ontology. Secondly, similarity calculation is composed of two
methods: concept similarity and instance similarity are proposed and implemented in
the prototype system. | en_US |