@inproceedings{0b0d68918ac94672ac32907653d4e2a8,
title = "A data streams clustering algorithm based on interval data",
abstract = "Data stream mining has become a new research direction in recent years, and clustering analysis based on data stream has become a hot spot. Based on Squeezer cluster algorithm, ID-Squeezer, a new algorithm, is proposed, which scores clustering results by interval data and adjusts the upper and lower limits dynamically according to new data within threshold. The algorithm effectively reduces the storage space and retains information of cluster result. The experiment demonstrates the effectiveness of the algorithm we proposed. Copyright",
keywords = "Clustering analysis, Data stream, Interval data, Squeezer",
author = "Yan Li and Ming Ye and Huiwen Wang and Dan Liu and Yin Che",
year = "2008",
language = "英语",
isbn = "9781627486828",
series = "38th International Conference on Computers and Industrial Engineering 2008",
pages = "2775--2778",
booktitle = "38th International Conference on Computers and Industrial Engineering 2008",
}