In this position paper, we discuss recent applications of simulation approaches for recommender systems tasks. In particular, we describe how they were used to analyze the problem of misinformation spreading and understand which data characteristics affect the performance of recommendation algorithms more significantly. We also present potential lines of future work where simulation methods could advance the work in the recommendation community.

翻译：在本立场文件中,我们讨论了最近应用模拟方法执行推荐人系统任务的问题,特别是我们介绍了如何利用模拟方法分析错误信息传播问题,并更清楚地了解哪些数据特性影响建议算法的绩效,我们还介绍了模拟方法可推动推荐人工作的未来工作方针。