The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 52-507
Full Name: Shao-Shin Hung
Position: Assistant Professor
Age: ON
Sex: Male
Address: No. 196, Section 4, Ho-Nai Rd, Taichung
Country: TAIWAN
Tel: 886-5-2267125-51301
Tel prefix: 886
Fax: 886-5-226-8417
E-mail address: hss@cs.ccu.edu.tw
Other E-mails: hss@cs.ccu.edu.tw
Title of the Paper: A Study on Ontology Structure Matching
Authors as they appear in the Paper: Li-Hua Li, Rong-Wang Hsu, Shao-Shin Hung, Yu-Chien Chou, and Tsung-Jen Pu
Email addresses of all the authors: lhli@cyut.edu.tw, 2ronger@wfu.edu.tw, hss@cs.ccu.edu.tw, 4alex.chou@yahoo.com.tw, 5s714608@cyut.edu.tw
Number of paper pages: 11
Abstract: Intelligent Web employs the capabilities of high speed networks and exploits the parallel advancements in Internet-based technologies such as the Semantic Web, Web Services, Agent-based Technologies, and context awareness. Nonetheless current study environment still lacks significant exploration in this field. In view of this, the study established mobile message template using Generally in the field of ontology, much emphasis is placed on how to apply ontology information; whereas few studies explore the efficacy of matching while more emphasize on how to match with respect to ontology matching. Under current mobile-commerce environment, the content of messages conveyed by shops mostly renders in texts. Consequently efficiency becomes the most important key to consideration. This article will conduct structural similarity matching through ontology structure, exploring the efficacies generated via different methods, and matching the two types of traditional ontolog!
y: Performance assessment was conducted using Breadth-First-Matching (BFM), Depth-First-Matching (DFM) and Node-Index-Matching (NIM) proposed by the study, in order to determine the most suitable method based on the numbers of matching. The experimental data showed that Node-Index-Matching (NIM) proposed by the study had significantly optimal performance on efficacy assessment, which consequently is more suitable for use in mobile environment with large quantity of messages.
Keywords: Ontology, Ontology Matching, Breadth-First-Matching (BFM), Depth-First-Matching (DFM), Mobile Message
EXTENSION of the file: .pdf
Special (Invited) Session: No.
Organizer of the Session: No.
How Did you learn about congress: Knowledge and Data Technology, File Structures and Design and Data Bases
IP ADDRESS: 163.28.96.10
