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- W2103803708 abstract "This paper presents an innovative approach for learning the distinctive attributes of uncertain objects. The proposed system takes instances, clusters them into different concepts and consequently induces a hierarchy which is used for later classification. We introduce the major steps of the approach using a set of city attributes and further illustrate the applicability for a real world problem, namely the learning of structural concepts of business letters." @default.
- W2103803708 created "2016-06-24" @default.
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- W2103803708 date "2002-11-22" @default.
- W2103803708 modified "2023-09-26" @default.
- W2103803708 title "Selecting distinctive attributes for concept learning" @default.
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- W2103803708 doi "https://doi.org/10.1109/kes.1997.616851" @default.
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