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Bridging Real World Semantics to Model World Semantics for Taxonomy Based Knowledge Representation System

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Abstract

As a mean to map ontology concepts, a similarity technique is employed. Especially a context dependent concept mapping is tackled, which needs contextual information from knowledge taxonomy. Context-based semantic similarity differs from the real world similarity in that it requires contextual information to calculate similarity. The notion of semantic coupling is introduced to derive similarity for a taxonomy-based system. The semantic coupling shows the degree of semantic cohesiveness for a group of concepts toward a given context. In order to calculate the semantic coupling effectively, the edge counting methods is revisited for measuring basic semantic similarity by considering the weighting attributes from where they affect an edge’s strength. The attributes of scaling depth effect, semantic relation type, and virtual connection for the edge counting are considered. Furthermore, how the proposed edge counting method could be well adapted for calculating context-based similarity is showed. Through experimental results are provided for both edge counting and context-based similarity. The results of proposed edge counting were encouraging compared with other combined approaches, and the context-based similarity also showed understandable results. The novel contributions of this paper come from two aspects. First, the similarity is increased to the viable level for edge counting. Second, a mechanism is proviede to derive a context-based similarity in taxonomy-based system, which has emerged as a hot issue in the literature such as Semantic Web, MDR, and other ontology-mapping environments.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Software System Laboratory, Korea University, 1, 5-ka Anam-dong, Sungbuk-ku, Seoul, 136-701, Korea

    Ju-Hum Kwon, Chee-Yang Song & Doo-Kwon Baik

  2. Department of Computer Science, Konkuk University, 322 Danwol-dong, Chungju-si, Chungcheongbuk-do, 380-701, Korea

    Chang-Joo Moon

Authors
  1. Ju-Hum Kwon
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  2. Chee-Yang Song
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  3. Chang-Joo Moon
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  4. Doo-Kwon Baik
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Correspondence to Chang-Joo Moon.

Additional information

Ju-Hum Kwon is a Ph.D. candidate in the Department of Computer Science and Engineering at Korea University. He received his master’s degree in electrical and computer engineering from Wayne State University. His research interests include ontological foundations of knowledge representation with special emphasis on reasoning on taxonomic structure and ontology integration. He was a project manager at central data processing center in Korea Air Force.

Chee-Yang Song is a researcher at the Service Research Center in Korea Telecom Company, Korea. He received the Ph.D. degree from Korea University in 2003, the B.S. degree from Hannam University and the M.S. degree from Chungang University in 1985 and 1987, respectively. His current research areas include UML modeling technology, software architecture, integration of modeling methods and formal specification, metamodel and semantics.

Chang-Joo Moon is a research professor at the Korea University. He received his master’s and Ph.D. degrees from Korea University in 1998 and 2004, respectively. His research areas include database system, information integration system, and computer security with special emphasis on user authentication for OSGi environment.

Doo-Kwon Baik is a professor at the Korea University. He received his master’s and Ph.D. degrees in computer science from Wayne State University respectively. His research interests include data engineering, software engineering, modeling and simulation. He served as a chair in ISO/IEC JTC1/SC32-Korea. He has also served as a president of the Korea Simulation Society.

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Kwon, JH., Song, CY., Moon, CJ. et al. Bridging Real World Semantics to Model World Semantics for Taxonomy Based Knowledge Representation System. J Comput Sci Technol 20, 296–308 (2005). https://doi.org/10.1007/s11390-005-0296-6

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  • DOI: https://doi.org/10.1007/s11390-005-0296-6

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