The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Mining data streams: a review
Abstract
The recent advances in hardware and software have enabled the capture of different measurements of data in a wide range of fields. These measurements are generated continuously and in a very high fluctuating data rates. Examples include sensor networks, web logs, and computer network traffic. The storage, querying and mining of such data sets are highly computationally challenging tasks. Mining data streams is concerned with extracting knowledge structures represented in models and patterns in non stopping streams of information. The research in data stream mining has gained a high attraction due to the importance of its applications and the increasing generation of streaming information. Applications of data stream analysis can vary from critical scientific and astronomical applications to important business and financial ones. Algorithms, systems and frameworks that address streaming challenges have been developed over the past three years. In this review paper, we present the state-of-the-art in this growing vital field.
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Cites
Hand, D. J., Mannila, H., & Smyth, P. (2001) · Cited by 2,581
Models and issues in data stream systems
Babcock, B., Babu, S., Datar, M., Motwani, R., & Widom, J. (2002) · Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems · doi:10.1145/543613.543615 · Cited by 2,495
Mining high-speed data streams
Domingos, P., & Hulten, G. (2000) · Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/347090.347107 · Cited by 2,185
A Framework for Clustering Evolving Data Streams
Aggarwal, C. C., Yu, P. S., Han, J., & Wang, J. (2003) · Proceedings 2003 VLDB Conference · doi:10.1016/b978-012722442-8/50016-1 · Cited by 1,808
A symbolic representation of time series, with implications for streaming algorithms
Lin, J., Keogh, E., Lonardi, S., & Chiu, B. (2003) · Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery · doi:10.1145/882082.882086 · Cited by 1,799
Mining time-changing data streams
Hulten, G., Spencer, L., & Domingos, P. (2001) · Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/502512.502529 · Cited by 1,748
Smith, A. (2002) · Artificial Intelligence in Medicine · doi:10.1016/s0933-3657(02)00058-1 · Cited by 1,700
Data Streams: Algorithms and Applications
Muthukrishnan, S. (2005) · now publishers, Inc. eBooks · doi:10.1561/9781933019604 · Cited by 1,433
Mining concept-drifting data streams using ensemble classifiers
Wang, H., Fan, W., Yu, P. S., & Han, J. (2003) · Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/956750.956778 · Cited by 1,256
Approximate frequency counts over data streams
Manku, G. S., & Motwani, R. (2012) · Proceedings of the VLDB Endowment · doi:10.14778/2367502.2367508 · Cited by 1,178
Cited by
A survey on concept drift adaptation
Gama, J., Žliobaitė, I., Bifet, A., Pechenizkiy, M., & Bouchachia, A. (2014) · ACM Computing Surveys · doi:10.1145/2523813 · Cited by 3,735
Chen, M., Mao, S., & Liu, Y. (2014) · Mobile Networks and Applications · doi:10.1007/s11036-013-0489-0 · Cited by 2,913
Toward Scalable Systems for Big Data Analytics: A Technology Tutorial
Hu, H., Wen, Y., Chua, T.-S., & Li, X. (2014) · IEEE Access · doi:10.1109/access.2014.2332453 · Cited by 1,099
A survey of multiple classifier systems as hybrid systems
Woźniak, M., Graña, M., & Corchado, E. (2014) · Information Fusion · doi:10.1016/j.inffus.2013.04.006 · Cited by 912
Webb, G. I., Hyde, R., Cao, H., Nguyen, H. L., & Petitjean, F. (2016) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-015-0448-4 · Cited by 536
Metadata
- Authors
- Gaber, M. M., Zaslavsky, A., & Krishnaswamy, S.
- Venue
- ACM SIGMOD Record
- Published
- 2005-06
- Volume
- 34
- Issue
- 2
- Pages
- 18-26
- ISSN
- 0163-5808 (ISSN-L)
- OpenAlex
- W2119939946
- Cited by
- 886
- References
- 44
- FWCI
- 36.07
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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