Abstract
A critical capability required for operating in today’s information overload is the ability to aggregate information from disparate sources into a unified coherent form. To date, almost majority contents of shopping mall are built by technology that is not regarding as integration and extension. We need to make a meta-data and product lists additionally if we want to use comparison-shopping. However, this meta-data does not contain semantics, it can only serve text searching. For this reason, a buyer wastes time costs to get any information in which they are really interested. Moreover, comparison shopping malls are adapted by their own technology; therefore it is also impossible to share their products information. In this paper, we use semantic web technology DAML+OIL. By using this, we make ontology for each shopping mall, and we define concept and structure and we made DAML markup instance data, then extracted semantic factors using DAMLJessKB. We also used these extracted semantic factors as a fact for the JESS inference engine, so that we can make it possible to inference and provide reasoning in web data structures. Our approach allows inference to be carried out when a query is processed and done. Thereby, to validate our approach, we have implemented a working prototype based on and then used the above semantic web inference-system.
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Lee, HK., Yu, YH., Ghose, S., Jo, GS. (2004). Comparison Shopping Systems Based on Semantic Web – A Case Study of Purchasing Cameras. In: Li, M., Sun, XH., Deng, Qn., Ni, J. (eds) Grid and Cooperative Computing. GCC 2003. Lecture Notes in Computer Science, vol 3032. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24679-4_27
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DOI: https://doi.org/10.1007/978-3-540-24679-4_27
Publisher Name: Springer, Berlin, Heidelberg
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