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Titlebook: Advances in Case-Based Reasoning; 9th European Confere Klaus-Dieter Althoff,Ralph Bergmann,Alexandre Hanf Conference proceedings 2008 Sprin

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期刊全称Advances in Case-Based Reasoning
期刊简称9th European Confere
影响因子2023Klaus-Dieter Althoff,Ralph Bergmann,Alexandre Hanf
视频video
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Advances in Case-Based Reasoning; 9th European Confere Klaus-Dieter Althoff,Ralph Bergmann,Alexandre Hanf Conference proceedings 2008 Sprin
影响因子This volume contains the papers presented at the 9th European Conference on Case-Based Reasoning (ECCBR 2008). Case-based reasoning (CBR) is an arti?cial intelligence approach whereby new problems are solved by remembering, adapting and reusing solutions to a previously solved, similar problem. The collection of previously solved problems andtheirassociatedsolutionsisstoredinthecasebase. Neworadaptedsolutions are learned and updated in the case base as needed. In remembrance of the First European Workshop on Case-Based Reasoning, which took place 15 years ago at the European Academy Otzenhausen, not far from Trier, this year’s conference was especially devoted to the past, present, and future of case-based reasoning. ECCBR and the International Conference on Case-Based Reasoning (IC- CBR) alternate every year. ECCBR 2008 followed a series of seven successful European workshops previously held in Otzenhausen, Germany (1993), Ch- tilly, France (1994), Lausanne, Switzerland (1996), Dublin, Ireland (1998), and Trento, Italy (2000), and three European conferences in Aberdeen, UK (2002), ¨ Madrid, Spain (2004), and Olu ¨deniz/Fethiye, Turkey (2006). The International Conferences on Case-
Pindex Conference proceedings 2008
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Building a traditional Kurdish Cityntial papers and illustrate the life-cycle of research themes over the last fifteen years. The insights afforded by this analysis are presented in detail. In addition to the analysis of the sub-structure of CBR research, this paper also presents some global statistics on the CBR conference literature.
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Building an Enterprise Architecture Practicem the potentially enormous space of possibilities, it proposes personalizing adaptations based on learned information about user preferences. Evaluations of the system are encouraging for the use of knowledge planning and learned preference information to improve adaptation performance.
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0302-9743 an arti?cial intelligence approach whereby new problems are solved by remembering, adapting and reusing solutions to a previously solved, similar problem. The collection of previously solved problems andtheirassociatedsolutionsisstoredinthecasebase. Neworadaptedsolutions are learned and updated in
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