| Title: | Improvement of Perception through Task Executions. |
| Authors: | Ryohei Orihara, Tomoko Murakami, Takehiko Yokota, and Naomichi Sueda |
| Series: | Linköping Electronic Articles in Computer and Information Science ISSN 1401-9841 |
| Issue: | Vol. 5 (2000): nr 033 |
| URL: | http://www.ep.liu.se/ea/cis/2000/033/ |
| Abstract: |
Good perception is indispensable to perform problem solving
well. This is a common issue in cognitive psychology, but has
been seldom studied in artificial intelligence. We formalize
a perception scheme for an intelligent software using
vector spaces. We also construct an experimental system
for text documents and still images. Using the system for the
texts, we conduct experiments in a context of information
retrieval. The experiments using FAQ (Frequently Asked
Questions) documents prove the method to be outperforming
the conventional method. As for the system for the images,
we extract common features out of a certain set of images in
terms of Kansei engineering. The features explain characteristics
of the images in intuitive manner. We aim to construct a
decision support system, which cna analyze multimedia
data from various viewpoints; however we will need to extend
the method in various ways to achieve that.
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Original publication 2000-12-21 |
Postscript part I --
Checksum Postscript part II -- Checksum II |
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