We study selectivity estimation techniques for set similarity queries. A wide variety of similarity measures for sets have been proposed in the past. In this work we concentrate o...
Marios Hadjieleftheriou, Xiaohui Yu, Nick Koudas, ...
We study the problem of estimating selectivity of approximate substring queries. Its importance in databases is ever increasing as more and more data are input by users and are in...
In this paper we address the problem of selecting variables or features in a regression model in the presence of both additive (vertical) and leverage outliers. Since variable sel...
Many database applications have the emerging need to support fuzzy queries that ask for strings that are similar to a given string, such as “name similar to smith” and “tele...
In a variety of applications ranging from optimizing queries on alphanumeric attributes to providing approximate counts of documents containing several query terms, there is an in...
Zhiyuan Chen, Flip Korn, Nick Koudas, S. Muthukris...