Aesthetical concept for human-computer interaction using fuzzy knowledge base clustering
This paper attempts to reduce the complexity of aesthetical conceptual system rule base by using fuzzy clustering method to make our decision making nearer to human computer interaction ideals by using the concept of similarity. Where we have a rule base of our aesthetical concept called Aesthetical...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2007
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/3121/1/Reza-CITA-paper180-1.pdf http://eprints.utm.my/id/eprint/3121/ |
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| Institution: | Universiti Teknologi Malaysia |
| Language: | English |
| Summary: | This paper attempts to reduce the complexity of aesthetical conceptual system rule base by using fuzzy clustering method to make our decision making nearer to human computer interaction ideals by using the concept of similarity. Where we have a rule base of our aesthetical concept called Aesthetical Fuzzy Rule Base (AFRB) we have numbers of aesthetical concept rules. To make our AFRB more usable and preparing it for better interaction with human, it must be clustered, whereas we are dealing in our interaction with computer by uncertainties of aesthetical semantics. Finally, we will show an appropriate clustering called fuzzy clustering by reasoning for our AFRB. |
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