Titlebook: Case-Based Approximate Reasoning; Eyke Hüllermeier Book 2007 Springer Science+Business Media B.V. 2007 artificial intelligence.case-based

尊重

Constraint-Based Modeling of Case-Based Inference,arity of associated outcomes in the form of a lower bound. A related inference mechanism then allows for realizing CBI as a kind of constraint propagation. We also discuss representational issues and algorithms for putting the idea of . within this framework into action. The chapter is organized as

小口啜饮

ABOUT

Conclusions and Outlook,ved cases (a case base consisting of input-output tuples) in order to predict a set of promising candidate outputs given a new query input. The corresponding inference schemes are based on suitable formalizations of the heuristic assumption that similar inputs yield similar outputs. Proceeding from

TERRA

A Framework for Ontology Learningarity of associated outcomes in the form of a lower bound. A related inference mechanism then allows for realizing CBI as a kind of constraint propagation. We also discuss representational issues and algorithms for putting the idea of . within this framework into action. The chapter is organized as

失望未来

Ontology — Definition & Overviewing has been pointed out recently [99, 407]. Besides, some attempts at combining case-based reasoning (or, more generally, analogical reasoning) and methods from fuzzy set theory have already been made [408], including the use of fuzzy sets for supporting the computation of similarities of situation

Initiative

出来

Eyke HüllermeierMajor contribution to the methodical foundations of case-based reasoning.Builds bridges between the fields of CBR and approximate reaoning.First monograph of this type

Longitude

Theory and Decision Library Bhttp://image.papertrans.cn/c/image/222308.jpg

有危险

收养

https://doi.org/10.1007/978-1-4615-0925-7This chapter serves two purposes. Firstly, we provide some background information on similarity-based reasoning and related topics. Secondly, we introduce a formal framework of . (CBI) that provides the basis for the methods which are developed in subsequent chapters.