Applying Ontology to Relevant Document Discovery

• Main Authors: Liang-Lu Shih, 施亮如
• Other Authors: None
• Format: Others
• Language: en_US
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/wq7mn4

碩士 === 國立中央大學 === 資訊管理研究所 === 94 === 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.