Database Reference
In-Depth Information
Giannella, C., Han, J. W., Pei, J., Yan, X. F., &
Yu, P. S. (2003). Mining frequent patterns in
data streams at multiple time granularities.
Data
Mining: Next Generation Challenges and Future
Directions
, AAAI/MIT.
Li, H. F., Ho, C. C., Kuo, F. F., & Lee, S. Y. (2006)
A new algorithm for maintaining closed frequent
itemsets in data streams by incremental updates.
Six IEEE International Conference on Data Min-
ing Workshop
.
Guha, S., & Koudas, N. (2002). Approximating
a data stream for querying and estimation: Algo-
rithms and performance evaluation.
International
Conference on Data Engineering
.
Li, H. F., Lee, S. Y., & Shan, M. K. (2004). An
efficient algorithm for mining frequent itemsets
over the entire history of data streams.
The In-
ternational Workshop on Knowledge Discovery
in Data Streams
.
Halatchev, M., & Gruenwald, L. (2005). Estimat-
ing missing values in related sensor data streams.
International Conference on Management of
Data
.
Lin, C. H., Chiu, D. Y., Wu, Y. H., & Chen, A.
L. P. (2005). Mining frequent itemsets from data
streams with a time-sensitive sliding window.
SIAM International Conference on Data Min-
ing
.
Jiang, N., & Gruenwald, L. (2006). CFI-Stream:
Mining Closed Frequent Itemsets in Data Streams.
ACM SIGKDD international conference on knowl-
edge discovery and data mining
.
Manku, G. S., & Motwani, R. (2002).Approximate
frequency counts over data streams.
International
Conference on Very Large Databases
.
Jiang, N., & Gruenwald, L. (2007). Estimating
missing data in data streams,
the International
Conference on Database Systems for Advanced
Applications
.
Mozafari, B., Thakkar, H., & Zaniolo, C. (2008).
Verifying and mining frequent patterns from large
windows over data streams.
IEEE International
Conference on Data Engineering
.
Kargupta, H., Bhargava, R., Liu, K., Powers, M.,
Blair, P., Bushra, S., et al. (2004). VEDAS: A mo-
bile and distributed data stream mining system for
real-time vehicle monitoring.
SIAM International
Conference on Data Mining
.
Shin, S. J., & Lee, W. S. (2007). An online inter-
active method for finding assoication rules data
streams.
ACM 16th Conference on Information
and Knowledge Management
.
Koh, J. L., & Shin, S. N. (2006). An approximate
approach for mining recently frequent itemsets
from data streams.
The 8th International Con-
ference on Data Warehousing and Knowledge
Discovery
.
Yang, L., & Sanver, M. (2004). Mining short as-
sociation rules with one database scan;
Interna-
tional Conference on Information and Knowledge
Engineering
.
Yu, J. X., Chong, Z. H., Lu, H. J., & Zhou, A. Y.
(2004). False positive or false negative: Mining
frequent itemsets from high speed transactional
data streams.
International Conference on Very
Large Databases
.
Li, H. F., & Cheng, H. (2008). Improve frequent
closed itemsets mining over data stream with
bitmap.
Ninth ACIS International conference on
software engineering, artificial intelligence, net-
working, and parallel/distributed computing
.
Zhu, Y. Y., & Shasha, D. (2002). StatStream: Sta-
tistical monitoring of thousands of data streams
in real time.
International Conference on Very
Large Databases
.
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