A Large-Scale System Evaluation on Component-Level
作者： Jens Kürsten , Maximilian Eibl
DOI: 10.1007/978-3-642-20161-5_69
关键词: Baseline (configuration management) 、 Set (abstract data type) 、 System evaluation 、 Text corpus 、 Computer science 、 Component (UML) 、 Data mining 、 Scale (map)
摘要: This article describes a large-scale empirical evaluation across different types of English text collections. We ran about 140,000 experiments and analyzed the results on system component-level to find out if we can select configurations that perform reliable specific corpora. To our own surprise observed set configuration parameters achieved 95% optimal average MAP all conclude this could be used as baseline reference for new IR approaches
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