Search engine configuration can be quite difficult for inexpert developers. Instead, an auto-configuration approach can be used to speed up development time. Yet, such an automatic process usually requires relevance labels to train a supervised model. In this work, we suggest a simple solution based on query performance prediction that requires no relevance labels but only a sample of queries in a given domain. Using two example usecases we demonstrate the merits of our solution.

翻译：对专家开发者来说,搜索引擎配置可能相当困难。 相反,可以使用自动配置方法加快开发时间。 然而,这样的自动程序通常需要相关的标签来训练一个受监督的模型。 在这项工作中,我们建议基于查询性能预测的简单解决方案,不需要相关标签,而只需要特定域的查询样本。我们用两个示例来展示我们解决方案的优点。