Transcript Yu - University of Illinois at Chicago

Mining Traffic Stream and
Vehicle/pedestrian Networks
Philip S. Yu
Professor & Wexler Chair in Information Technology
Computer Science Department
University of Illinois at Chicago
Problem Statement and Motivation
• With the advancement on sensor, GPS and
wireless technologies, transportation system
transforms from data poor to data rich.
• Challenges:
• Real-time requirement
• Complexity of the data
• Spatio-temporal correlation
• Noisy or uncertain data
• Privacy preservation
Prediction of congested areas
GPS applications
- database compaction through object simplification
- faster pattern matching
3
Collision Detection
collision detection can be more efficient using segmentation
- approximate object movement
4
Technical Approach
• Develop real-time stream processing capability
to address monitoring type applications
• Develop new scalable mining techniques to
discover traffic and traversal patterns
• Explore graph OLAP technique to zoom in/out a
huge graph for analysis on different granularities
• Explore learning from heterogeneous sources to
address lacking of training examples
Key Achievements and Future Goals
• Real-time data stream mining algorithms
with concept drifts, and uncertainty
• Indexing and similarity search methods for
trajectories
• Online Analytical Processing paradigms
for Information Network
• Privacy preservation techniques
• Learning from heterogeneous examples
• Explore green technology
Publications
• C. Aggarwal, P.S. Yu, "A Framework for Clustering Uncertain Data
Streams", IEEE Intl. Conf. on Data Engineering, 2008.
• A. Anagnostopoulos, M. Vlachos, E. Keogh, P.S. Yu, "Global
Distance-based Segmentation of Trajectories", ACM KDD 2006.
• C. Aggarwal, P.S. Yu, "Privacy-Preserving Data Mining: Models and
Algorithms", Springer, 2008.
• B. Fung, K. Wang, P.S.Yu, "Anonymizing Classification Data for
Privacy Preservation", IEEE Trans. Knowledge and Data Eng., Vol.
19, No. 5, May 2007.
• X. Shi, Q. Liu, W. Fan, Q. Yang, P.S. Yu, "Predictive Modeling with
Heterogeneous Sources", SIAM Data Mining Conference, 2010.
• C. Chen, X. Yan, F. Zhu, J. Han, P.S. Yu, "Graph OLAP: A Multidimensional Framework for Graph Data Analysis", Knowledge and
Information Systems, Vol. 21. No. 1, 2009.
Publications
• B. Gedik, L. Liu, P. S. Yu, "ASAP: An Adaptive Sampling Approach
to Data Collection in Sensor Networks", IEEE Trans. Parallel
Distributed Systems, 2007.
• B. Gedik, K.L. Wu, P.S. Yu, L. Liu, "MobiQual: QoS-aware Load
Shedding in Mobile CQ Systems", IEEE Intl. Conf. on Data
Engingeering, 2008.
• K.L. Wu, S.K. Chen, P.S. Yu, "Incremental Processing of Continual
Range Queries over Moving Objects", IEEE Trans. Knowledge and
Data Eng., Vol. 18, No. 11, 2006.
• W. Li, W.K. Ng, X.H. Dang, K. Zhang, P.S. Yu, "Density-Based
Clustering of Data Streams at Multiple Resolutions", ACM Trans.
Knowledge Discovery from Data, Vol. 3, No. 3, 2009.
• X. Gu, S. Papadimitriou, P.S. Yu, S.P. Chang "Toward Learningbased Failure Management for Distributed Stream Processing
Systems", IEEE Intl. Conf. on Distributed Computing Systems, 2008.