COUNTATA
COUNTATA
复制标题
康塔塔
DOI:
--
复制
发表时间:
2020
影响因子:
2.5
通讯作者:
H. V. Jagadish
中科院分区:
文献类型:
--
作者:
Y. Moskovitch;H. V. Jagadish
Information regarding the counts of attributes combination is central to the profiling of a data set. It may reveal bias; it can help determine fitness for use. While counts of individual attribute values may be stored in some data set profiles, there are too many combinations of attributes for it to be practical to store counts for each combination. To this end, we present the notion of storing a "label" of limited size that can be used to obtain good estimates for these counts. A label contains information regarding the count of selected patterns-attributes values combinations-in the data. We define an estimation function, that uses this label to estimate the count of every pattern. Intuitively, there is a trade-off between the label size and its estimation error. We propose a demonstration of Countata, a system that allows the user to examine this trade-off as well as the label's count information. We will demonstrate the usefulness of Countata using real-life data, and illustrate the effectiveness of our estimation paradigm.
DOI:
--
发表时间:
2019
期刊:
A Quarterly bulletin of the Computer Society of the IEEE Technical Committee on Data Engineering
影响因子:
--
作者:
Stoyanovich, Julia;Howe, Bill
通讯作者:
Howe, Bill
DOI:
10.1145/3357384.3357853
发表时间:
2019-11
期刊:
Proceedings of the 28th ACM International Conference on Information and Knowledge Management
影响因子:
--
作者:
Chenkai Sun;Abolfazl Asudeh;H. V. Jagadish;Bill Howe;Julia Stoyanovich
通讯作者:
Chenkai Sun;Abolfazl Asudeh;H. V. Jagadish;Bill Howe;Julia Stoyanovich
DOI:
10.1109/icde51399.2021.00184
发表时间:
2021
期刊:
{ICDE}
影响因子:
--
作者:
Moskovitch, Yuval;Jagadish, H. V.
通讯作者:
Jagadish, H. V.