Extensions of Histogram Construction Algorithms for Interval Data

Histogram is one of tools that efficiently summarize data, and it is widely used for selectivity estimation and approximate query answering. Existing histogram construction algorithms are applicable to point data represented by a set of values. As often as point data, we can meet interval data such as daily temperature and daily stock prices. In this paper, we thus propose the histogram construction algorithms for interval data by extending several methods used in existing histogram construction algorithms. Our experiment results, using synthetic data, show our algorithms outperform naive extension of existing algorithms.