Titlebook: Case-Based Reasoning; A Textbook Michael M. Richter,Rosina O. Weber Textbook 2013 Springer-Verlag GmbH Germany 2013 Artificial intelligence

MILL

Uncertaintyly in applications. Of special interest is the relation to similarity. The rough set concept provides a method of describing uncertain results in a user-controlled way. Fuzzy sets and their logical descriptions are introduced. Examples show the relations between fuzzy sets and CBR. In addition, poss

conference

Probabilitiesenomena. Some basic knowledge about probabilities is required. We discuss that the connections between similarities and probabilities are manifold. There are two directions: Probabilities give rise to adequate similarity measures. First we introduced covariance and correlation measures and the Kullb

博愛家

https://doi.org/10.1007/978-3-642-40167-1Artificial intelligence; Case-based reasoning (CBR); Complex knowledge; Information retrieval; Knowledge

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Michael M. Richter,Rosina O. WeberFirst English-language textbook on the topic.Coauthor among the pioneers of the subject.Content thoroughly class-tested, book features chapter summaries, background notes, and exercises throughout.Inc

Armada

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費解

Advances in Information Technologies,ly an interest in learning about it. It e positions case-based reasoning (CBR) in its scientific, educational, and applied contexts; it is therefore crucial for anyone interested in learning or teaching CBR. It provides a very intuitive notion of the CBR reasoning paradigm that can be understood by

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