Titlebook: Case-Based Reasoning Research and Development; 19th International C Ashwin Ram,Nirmalie Wiratunga Conference proceedings 2011 Springer-Verl

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词汇表

终端

Invariants of One-Factorizations,ttleneck in this work has often been the development of case libraries needed to support this reasoning rather than the transformation of the cases themselves. In much of our work, we have taken an approach in which we treat web-recourses as the distributed knowledge engineering that can be integrat

跳脱衣舞的人

As Close to Perfection As Humanly Possibleng Jeopardy! questions is text from written sources such as encyclopedias or news articles. A text passage may partially or fully indicate that some candidate answer is the correct answer to the question. Recognizing whether it does requires determining the extent to which what the passage is saying

省略

As Close to Perfection As Humanly Possible One might think that with the definition of commonalities and differences, the definition of similarities in and for ontologies should follow immediately. Traditionally, however, the contrary is true, because the method background of ontologies, i.e. logics-based representations, and similarity, i.

引导

引导

Clinch

https://doi.org/10.1007/978-1-4757-2834-7e select three different complexity measures and use them to evaluate eight case base editing algorithms. While we might expect the complexity of a case base to decrease, or stay the same, and the classification accuracy to increase, or stay the same, after maintenance, we find many counter-examples

强制令

Mathematical Fundamentals of Optimal Controlssive way, then adapting the source cases corresponding to the generalised target problem. This paper shows how enriching this ontology improves the retrieval and final results of the CBR system. An existing ontology is enriched by automatically adding new classes that will refine the initial organi

挥舞

Mathematical Fundamentals of Optimal Controlsally applicable methodological framework for CBR on the basis of formal concepts and methods for knowledge representation and reasoning with preferences. A preference-based approach to CBR appears to be appealing for several reasons, notably because case-based experiences naturally lend themselves