@inproceedings{f51666ff1b6c486caac1acd068b8bd49,
title = "Detecting Change in Data Streams",
abstract = "Detecting changes in a data stream is an important area of research with many applications. In this paper, we present a novel method for the detection and estimation of change. In addition to providing statistical guarantees on the reliability of detected changes, our method also provides meaningful descriptions and quantification of these changes. Our approach assumes that the points in the stream are independently generated, but otherwise makes no assumptions on the nature of the generating distribution. Thus our techniques work for both continuous and discrete data. In an experimental study we demonstrate the power of our techniques.",
author = "Daniel Kifer and Shai Ben-David and Johannes Gehrke",
note = "Publisher Copyright: {\textcopyright} VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases.; 30th International Conference on Very Large Data Bases, VLDB 2004 ; Conference date: 31-08-2004 Through 03-09-2004",
year = "2004",
doi = "10.1016/b978-012088469-8/50019-x",
language = "English (US)",
series = "VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases",
publisher = "Morgan Kaufmann Publishers, Inc.",
pages = "180--191",
editor = "Nascimento, \{Mario A.\} and Ozsu, \{M. Tamer\} and Donald Kossmann and Miller, \{Renee J.\} and Blakeley, \{Jose A.\} and Schiefer, \{K. Bernhard\}",
booktitle = "VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases",
address = "United States",
}