Advances in Case-Based Reasoning: 7th European Conference, by Agnar Aamodt (auth.), Peter Funk, Pedro A. González Calero

By Agnar Aamodt (auth.), Peter Funk, Pedro A. González Calero (eds.)

This publication constitutes the refereed court cases of the seventh eu convention on Case-Based Reasoning, ECCBR 2004, held in Madrid, Spain in August/September 2004.

The fifty six revised complete papers awarded including an invited paper and the summary of an invited speak have been conscientiously reviewed and chosen from eighty five submissions. All present matters in case-based reasoning, starting from theoretical and methodological matters to complex purposes in a variety of fields are addressed.

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Ak : CVk >}, where ai is an attribute name and the constraint CVi specifies the set of “allowable” values for attribute ai . By selecting only certain features for matching and imposing constraints on feature values, a context allows for controlling what can and what cannot be considered as a partial match: all (and only) cases that satisfy the specified constraints for the context are considered similar and are relevant with respect to the context. Machine learning and knowledge-mining techniques may be applied to determine an optimal context: selecting features which are most “relevant” for a given task and specifying characteristic values for them.

The key features of the framework infrastructure for methods along the main CBR tasks: Retrieve. Retrieval methods are organized around the tasks ObtainCases, AssessSim and Select. Since obtaining the cases is delegated to the Case Base, the methods in this category are mainly responsible for assessing similarity by parameterizing retrieval functionality. A number of similarity functions are provided both for local and aggregate similarity. Framework design imposes that similarity functions must be associated to specific individual types, the abstract constituents of cases.

There are two types of cases: (1) an input case (target) that describes the problem and is represented as a case without a solution; and (2) a source case, which is a case stored in a case-base that contains both a problem description and a solution. Using the information about the usefulness of individual attributes and information about their properties, attributes are grouped into two or more Telosstyle categories [36]. This enhancement of case representations is used during 26 Niloofar Arshadi and Igor Jurisica the retrieval process to increase the accuracy of classification and flexibility of retrieval, and to improve system’s performance.

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