Language and System

1. Hancock: A Language for Extracting Signatures from Data Streams, by Corinna Cortes, Kathleen Fisher, Daryl Pregibon, Anne Rogers, in the ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD) 2000.
2. Aurora: A Data Stream Management System (Demonstration), by D. Abadi, D. Carney, U. Cetintemel, M. Cherniack, C. Convey, C. Erwin, E. Galvez, M. Hatoun, J. Hwang, A. Maskey, A. Rasin, A. Singer, M. Stonebraker, N. Tatbul, Y. Xing, R.Yan, S. Zdonik, in the ACM International Conference on Management of Data (SIGMOD) 2003.
3. Models and issues in data stream systems, by B. Babcock, S. Babu, M. Datar, R. Motwani, J. Widom, in the ACM Symposium on Principles of Database Systems (PODS) 2002.
4. Query Languages and Data Models for Database Sequences and Data Streams, by Yan-Nei Law, Haixun Wang, Carlo Zaniolo, in the International Conference on Very Large Data Bases (VLDB) 2004.
5. ATLaS: A Native Extension of SQL for Data Mining, by Haixun Wang, Carlo Zaniolo, in the SIAM International Conference on Data Mining (SIAM DM) 2003.

   Change, Novelty Detection

   数据挖掘研究院

6. Online Novelty Detection on Temporal Sequences, by Junshui Ma, Simon Perkins, in the ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD) 2003.
7. A Framework for Diagnosing Changes in Evolving Data Streams, by Charu C. Aggarwal, in the ACM International Conference on Management of Data (SIGMOD) 2003.
8. Efficient Elastic Burst Detection in Data Streams, by Yunyue Zhu, Dennis Shasha, in the ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD) 2003.
9. Active Mining of Data Streams, by Wei Fan, Yi-an Huang, Haixun Wang, Philip S Yu, in the SIAM International Conference on Data Mining (SIAM DM) 2004.

   Clustering, Near-Neighbor Search

10. TECNO-STREAMS: Tracking Evolving Clusters in Noisy Data Streams with a Scalable Immune System Learning Model, by Olfa Nasraoui, Cesar Cardona Uribe, Carlos Rojas Coronel, in the IEEE International Conf. Data Mining (ICDM) 2003.
11. Clustering Binary Data Streams with Kmeans, by Carlos Ordonez, in the ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD) 2003.
12. Reverse Nearest Neighbor Aggregates Over Data Streams, by Flip Korn, S. Muthukrishnan, Divesh Srivastava, in the International Conference on Very Large Data Bases (VLDB) 2002.
13. A Framework for Clustering Evolving Data Streams, by Charu C. Aggarwal, Jiawei Han, Jianyong Wang, Philip S. Yu, in the International Conference on Very Large Data Bases (VLDB) 2003.
14. Streaming-Data Algorithms for High-Quality Clustering, by Liadan O'Callaghan, Nina Mishra, Adam Meyerson, Sudipto Guha, Rajeev Motawani, in the IEEE International Conference Data Engineering (ICDE) 2001.

    Synopsis Maintenance

15. Approximate Counts and Quantiles over Sliding Windows, by Arvind Arasu, Gurmeet Singh Manku, in the ACM Symposium on Principles of Database Systems (PODS) 2004.
16. Distributed TopK Monitoring, by Brian Babcock, Chris Olston, in the ACM International Conference on Management of Data (SIGMOD) 2003.
17. Maintaining Stream Statistics over Sliding Windows, by Mayur Datar, Aristides Gionis, Piotr Indyk, Rajeev Motwani, in the ACM-SIAM Symposium on Discrete Algorithms (SODA) 2002.
18. Maintaining Variance and k-Medians over Data Stream Windows, by Brian Babcock, Mayur Datar, Rajeev Motwani, LiadanO O'Callaghan, in the ACM Symposium on Principles of Database Systems (PODS) 2003.
19. StatStream: Statistical Monitoring of Thousands of Data Streams in Real Time, by Yunyue Zhu, Dennis Shasha, in the International Conference on Very Large Data Bases (VLDB) 2002.
20. Mining A Stream of Transactions for Customer Patterns, by Diane Lambert, Jose C. Pinheiro, in the ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD) 2001.
21. Approximate Medians and other Quantiles in One Pass and with Limited Memory, by Gurmeet Singh Manku, Sridhar Rajagopalan, Bruce G. Lindsay, in the ACM International Conference on Management of Data (SIGMOD) 1998.
22. Random Sampling Techniques for Space Efficient Online Computation of Order Statistics of Large Datasets, by Gurmeet Singh Manku, Sridhar Rajagopalan, Bruce G. Lindsay, in the ACM International Conference on Management of Data (SIGMOD) 1999.
23. Synopsis Data Structures for Massive Data Sets, by Phillip B. Gibbons, Yossi Matias, in the ACM-SIAM Symposium on Discrete Algorithms (SODA) 1999.