Collaborative knowledge discovery with Pasteur and Filter: a case of mixed-initiative intelligence
نویسنده
چکیده
This paper is based on the design of a system for collaborative knowledge discovery, in a situation where both some data and a domain expert are available. This system is composed of two elements: a data-mining algorithm (Pasteur) producing association rules organized in graphs, and a module (Filter) for collection, refinement and use of expert’s comments on the algorithm’s output. The two put together constitute an integrated environment for mixed-initiative knowledge discovery.
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