Abstract
Knowledge base is the foundation of intelligent system. It is very important to insure the consistency and non-redundancy of knowledge in knowledge base. The redundant, inclusive and incompatible knowledge must be processed in knowledge-integration due to variety of knowledge source. In this paper, we research the incompatible knowledge elimination approach in knowledge-integration based on rough set theory, and present a new knowledge-integration framework, which is effective to improve the efficiency of knowledge-integration.
This work was supported by National Natural Science Foundation of China, NO. 50378093.
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Guo, P., Ye, L., Fan, L. (2005). The Incompatible Knowledge Elimination in Knowledge-Integration. In: Li, D., Wang, B. (eds) Artificial Intelligence Applications and Innovations. AIAI 2005. IFIP — The International Federation for Information Processing, vol 187. Springer, Boston, MA. https://doi.org/10.1007/0-387-29295-0_10
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DOI: https://doi.org/10.1007/0-387-29295-0_10
Publisher Name: Springer, Boston, MA
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