Learning Organization in Global Intelligence

Masayuki Numao, Daishi Kato, and Masaru Yokoyama

We propose a cooperative system of human beings and computers, called Global Intelligence (GI). Human workers in GI are supported by a computer system called GIANT (GI Associating NeTwork), which consists of an inference mechanlsm by using a dynamically transforming network, and has a learning mechanism by adjusting a weight on each link in the network. After showing their structures and experiments, we point out that we can construct an interesting model of intelligence not only by analyzing a Society of Mind, but also by synthesizing Mind of a Society. For an experiment, the authors’ group constructed a filtering system for Internet news, which learns users’ interest automatically, and a WWW meta-search engine, which determines an appropriate search engine for a query. They are experimented with real data from several subjects, coBflrmi-g that they perform social filtering and personal filtering at the same time. We then propose a technique that hierarchically traces a reference history of a directory-type retrieval system, to collect socially general evaluation and evaluation of others who have the similar preference. The author implemented this technique as an information recommendation system, and verified that it recommends effectively based on less feedback.

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