@inproceedings{6f55c155d23542879e63406e0cb22bb4,
title = "Anomaly detection for continuous sequence based compression process",
abstract = "In some sequence anomaly detection tasks, discrete problem has solved preferable, it is a common continuous sequence contain much more complexity, which it widely grows in the industry demand. An appropriate method based on the compress and discrete technique can strongly improve the detect performance. we introduce an anomaly detect framework named SSAD, and get a good result when experiment the method on the UCR time series dataset.",
keywords = "Anomaly Detection, Continuous Sequence, Industry Data",
author = "Daren Yu and Huixin He and Gengfeng Zheng and Xiaoxian Zhang",
year = "2012",
doi = "10.1109/ICSESS.2012.6269480",
language = "英语",
isbn = "9781467320054",
series = "ICSESS 2012 - Proceedings of 2012 IEEE 3rd International Conference on Software Engineering and Service Science",
pages = "364--367",
booktitle = "ICSESS 2012 - Proceedings of 2012 IEEE 3rd International Conference on Software Engineering and Service Science",
note = "2012 IEEE 3rd International Conference on Software Engineering and Service Science, ICSESS 2012 ; Conference date: 22-06-2012 Through 24-06-2012",
}