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Mental Imagery Knowledge Representation Mode of Human-Level Intelligence System

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 5589)


For the human-level intelligence simulation we should simulate it from the essence of intelligence and with the research results of brain science, cognitive science, artificial intelligence and others. In our study, a mental imagery knowledge representation mode had been established based on cognitive mechanism of human. Two kinds of table named mental imagery concept attributes table and concept attribute value ranges table had been used together to represent mental imagery knowledge in system. Mental imagery concept attributes table which formed by the thought of concept lattice was used to decide relations among concepts and attributes under the circumstance of coarse granularity. While concept attribute value ranges table was used to record differences of individual objects belong to the same concept under the circumstance of fine granularity. The concrete structured method of tables and decision-making process of system were described in the paper. Finally, the validity and feasibility of the knowledge representation mode are illustrated with real examples.


  • Human-level intelligence
  • Knowledge representation mode
  • Mental imagery
  • Concept lattice
  • Discernible attribute matrix

This research was supported by country science support plan, China (NO2007BAE7B01).

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© 2009 Springer-Verlag Berlin Heidelberg

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Ke, H., Zhang, D., You, W. (2009). Mental Imagery Knowledge Representation Mode of Human-Level Intelligence System. In: Wen, P., Li, Y., Polkowski, L., Yao, Y., Tsumoto, S., Wang, G. (eds) Rough Sets and Knowledge Technology. RSKT 2009. Lecture Notes in Computer Science(), vol 5589. Springer, Berlin, Heidelberg.

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02961-5

  • Online ISBN: 978-3-642-02962-2

  • eBook Packages: Computer ScienceComputer Science (R0)