Count-Min-Log sketch: Approximately counting with approximate counters

Count-Min Sketch [1] is a widely adopted algorithm for approximate event counting in large scale processing. However, the original version of the Count-Min-Sketch (CMS) suers of some deciences, especially if one is interested in the low-frequency items, such as in textmining related tasks. Several variants of CMS [5] have been proposed to compensate for the high relative error for low-frequency events, but the proposed solutions tend to correct the errors instead of preventing them. In this paper, we propose the Count-Min-Log sketch, which uses logarithm-based, approximate counters [7, 4] instead of linear counters to improve the average relative error of CMS at constant memory footprint.