Event
Cube: An Organized Approach for Mining and Understanding Anomalous Aviation
Events
NASA NNX08AC35A (IVHM: Integrated
Vehicle Health Management) (01/01/08-12/31/10, Extended to 05/15/2012)
E-mail: hanj at cs.uiuc.edu
URL: http://www.cs.uiuc.edu/~hanj
List of Co-PIs and Collaborator
·
ChengXiang Zhai (co-PI): Department of Computer
Science, University of Illinois at Urbana-Champaign
·
Latifur Khan (co-PI): Department of Computer Science, University of Texas at Dallas
·
Vicent Ng (co-PI): Department of Computer Science, University of Texas at Dallas
·
Bhavani Thuraisingham (co-PI): Department
of Computer Science, University of
Texas at Dallas
·
Anne Kao
(Collaborator): Boeing
List of Supported Students and Staff
·
University of Illinois at Urbana-Champaign
o
Bolin Ding, Yanen
Li, Cindy Xide Lin, Jialu
Liu, Yinyao Yu, Duo Zhang, Bo Zhao
·
University of Texas at Dallas
o
Md. Arshad Ul
Abedin, Salim Ahmed, Greg Hellings, Qing Chen
Project Summary
Cyber-Physical
Systems (CPS) is a joint initiative between the Directorate for Computer and
Information Science and Engineering (CISE) and the Directorate for Engineering
(ENG). By abstracting from the particulars of specific application domains, the
CPS program aims to reveal cross-cutting fundamental scientific and engineering
principles that underpin the integration of cyber and physical elements across
all application sectors. The CPS program also supports the development of
methods and tools as well as hardware and software components, run-time
substrates, and systems based upon these principles to expedite and accelerate
the realization of cyber-physical systems in a wide range of applications.
Furthermore, the program aims to create a new research and education community
committed to the study and application of cyber-physical system innovations,
through the establishment of a CPS Virtual Organization (CPS-VO) and regular PI
meetings.
This project
represents a joint effort of two highly active and experienced researchers in
the fields of (i) data mining and information network analysis, and (ii)
physical/sensor networking and medical care network applications, respectively.
Combining our expertise and joining our research efforts, we propose to take care-net, i.e., medical care cyber-physical
network, as its key
application and investigate the foundations, methodologies, algorithms and
implementations of cyber-physical networks. In particular, we propose to study
three critical issues in the design and construction of cyber-physical
networks. (1) Rare event detection and analysis in
cyber-physical data streams,
including rare event detection, rare event analysis, and multidimensional
analysis for cyber-physical streams, (2) Reliable and trusted data
analysis with cyber-physical networks,
including veracity analysis for object consolidation and redundancy
elimination, entity resolution and information integration, and feedback interaction
between cyber- and physical- networks, and (3) Spatiotemporal
data analysis in cyber-physical networks, including spatiotemporal cluster analysis and
sequential pattern mining in cyber-physical networks and evolution of
cyber-physical networks. The research results are to be published in
various research and application forums and be integrated into the educational
programs at UIUC. The progress of the
project and the research results are also disseminated via the project Web site
(http://www.cs.uiuc.edu/homes/hanj/projs/cps.htm).
Publications
and Products:
Journal
articles
1. Hector Gonzalez, Jiawei Han, Hong Cheng, Xiaolei Li, Diego Klabjan, and Tianyi Wu, “Modeling Massive RFID
Datasets: A Gateway-Based Movement-Graph Approach",
IEEE Transactions on Knowledge and Data
Engineering, 22(1):90-104, 2010.
2.
TianyiWu,
Yuguo Chen, and Jiawei Han, “Re-Examination of
Interestingness Measures in Pattern Mining:
A Unified Framework", Data Mining and Knowledge Discovery, Jan. 2010.
3. Hongyan Liu, Yuan Lin, and Jiawei Han,
“Methods for Mining Frequent Items in Data Streams: An Overview", Knowledge
and Information Systems,
(Online: Nov 11, 2009) (DOI 10.1007/s10115-009-0267-2)
4. Jae-Gil Lee, Jiawei Han, Xiaolei Li, and Hong Cheng, “Mining Discriminative Patterns
for Classifying Trajectories on Road Networks", IEEE
Transactions on Knowledge and Data Engineering, 2010.
5. Xiaofei He, Deng Cai, Yuanlong Shao, Hujun Bao, and Jiawei Han, “Laplacian
Regularized Gaussian Mixture Model for Data Clustering", IEEE Transactions on Knowledge
and Data Engineering,
2010.
6. Duo Zhang, ChengXiang
Zhai, Jiawei Han, Ashok Srivastava, and Nikunj Oza, “Topic Modeling for
OLAP on Multidimensional Text Databases: Topic Cube and its Applications",
Statistical
Analysis and Data Mining,
2(5-6):378-395, 2009.
7. Hongyan Liu, Xiaoyu
Wang, Jun He, Jiawei Han, Dong Xin, Zheng Shao, “Top-down mining of frequent
closed patterns from very high dimensional data", Information Sciences, 179(7):899-924, 2009.
Book and Book Chapters
1.
Tarek
Abdelzaher, Mohammad Khan, Hieu
Le, Hossein Ahmadi, and Jiawei Han, “Data Mining for Diagnostic Debugging in Sensor
Networks: Preliminary Evidence and Lessons Learned", in Alfredo Cuzzocrea
(ed.), Intelligent Techniques for Warehousing and Mining Sensor Network Data, IGI
Global, 2010.
2.
Hector
Gonzalez, Jiawei Han, Hong Cheng, Tianyi Wu, “Warehousing
RFID and Location-BasedSensor Data",
Chapter 3 of Intelligent Techniques for Warehousing and Mining Sensor Network Data, Alfredo Cuzzocrea (ed.), IGI Global, 2009.
3.
Xifeng
Yan and Jiawei Han, “Graph Indexing", Edited by Charu C.
Aggarwal and Haixun Wang (eds.), Managing
and Mining Graph Data,
Kluwer Academic Publishers, 2009, pp. 143-164.
4.
Hong
Cheng and Xifeng Yan and Jiawei Han, “Mining
Graph Patterns",
Edited by Charu C. Aggarwal and HaixunWang
(eds.), Managing and Mining Graph Data,
Kluwer Academic Publishers, 2009, pp. 353-382.
5.
Harvey
J. Miller and Jiawei Han, “Geographic Data Mining and Knowledge Discovery: An
Overview", Harvey J.
Miller and Jiawei Han (eds.), Geographic Data Mining and Knowledge Discovery, 2nd ed.,
6.
Yvan
Bedard and Jiawei Han, “Fundamentals
of Spatial Data Warehousing and Geographic Knowledge Discovery", Harvey J. Miller and Jiawei
Han (eds.), Geographic Data Mining and Knowledge Discovery, 2nd ed.,
7.
Jiawei
Han, Jae-Gil Lee and Micheline Kamber, “An
Overview of Clustering Methods in Geographic Data Analysis", Harvey J. Miller and Jiawei
Han (eds.), Geographic Data Mining and Knowledge Discovery, 2nd ed., Taylor & Francis, 2009,
pp. 149-188.
8.
Jiawei
Han, “Data Mining",
in M. Tamer Ozsu and Ling Liu (eds.), Encyclopedia
of Database Systems,
Springer, 2009
9.
Hong
Cheng and Jiawei Han, “Frequent Itemsets and
Association Rules",
in M. Tamer Ozsu and Ling Liu (eds.), Encyclopedia
of Database Systems,
Springer, 2009
10. Hong Cheng and Jiawei Han, “Pattern-Growth
Methods", in M.
Tamer Ozsu and Ling Liu (eds.), Encyclopedia
of Database Systems,
Springer, 2009
11. Jiawei Han and Bolin Ding, “Stream
Mining", in M. Tamer
Ozsu and Ling Liu (eds.), Encyclopedia
of Database Systems,
Springer, 2009
12. Ronnie Alves, Joel Ribeiro,
13. Jiawei Han and Jing Gao, “Research
Challenges for Data Mining in Science and Engineering", in H. Kargupta,
et al., (eds.), Next Generation of Data Mining, Chapman & Hall/CRC, 2009,
pp.3-28.
14. Feida Zhu, Xifeng
Yan, Jiawei Han and Philip S. Yu, \Mining Frequent Approximate Sequential Patterns", in H. Kargupta,
et al., (eds.), Next Generation of Data Mining, Chapman & Hall/CRC, 2009, pp. 69-90.
15. Jiawei Han and Xiaolei
Li, “Classification and Clustering for Homeland Security", in John G. Voeller
(ed.), Wiley Handbook of Science and Technology for Homeland Security, John
Wiley & Sons, 2009.
Refereed Conference Publications
1. Ming Ji, Yizhou Sun, Marina Danilevsky
and Jiawei Han, “Graph Regularized Transductive
Classification on Heterogeneous Information Networks", Proc. 2010
European Conf. on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases (ECMLPKDD'10),
2.
Hyung Sul Kim, Sangkyum Kim, Tim Weninger, Jiawei Han, and Tarek Abdelzaher,
“NDPMine: Efficiently Mining Discriminative Numerical
Features for Pattern-Based Classification", Proc. 2010
European Conf. on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases (ECMLPKDD'10), Barcelona,
Spain, Sept. 2010.
3.
Mohammad M. Masud, Qing
Chen, Jing Gao, Latifur Khan, Jiawei Han, and Bhavani Thuraisingham, “Classification
and Novel Class Detection of Data Streams in a Dynamic Feature Space", Proc. 2010
European Conf. on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases (ECMLPKDD'10), Barcelona,
Spain, Sept. 2010.
4.
Zhenhui Li, Bolin
Ding, Jiawei Han, and Roland Kays, “Swarm:
Mining Relaxed Temporal Moving Object Clusters",
Proc. 2010 Int. Conf. on Very Large Data Bases (VLDB'10),
5.
Peixiang Zhao and
Jiawei Han, “On Graph
Query Optimization in Large Networks",
Proc. 2010 Int. Conf. on Very Large Data Bases (VLDB'10),
6.
Zhijun Yin,
Manish Gupta, Tim Weninger, and Jiawei Han, “A Unified
Framework for Link Recommendation Using Random Walks",
Proc. 2010 Int. Conf. on Advances in Social Networks Analysis and Mining
(ASONAM'10),
7.
Tim Weninger, Surya
Ramachandran, Daniel Greene, Jack Hart, Anand Kancherlapalli, William H. Hsu, and
Jiawei Han, “Speech-Assisted
Radiology System for Retrieval, Reporting and Annotation",
Proc. 2010 ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD'10),
(demo paper), Washington D.C., July 2010.
8.
Jing Gao, Feng Liang,Wei Fan, Chi Wang, Yizhou
Sun, and Jiawei Han, “Community
Outliers and their Efficient Detection in Information Networks",
Proc. 2010 ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD'10),
9.
Zhenhui Li, Bolin
Ding, Jiawei Han, Roland Kays, and Peter Nye, “Mining Hidden
Periodic Behaviors for Moving Objects", Proc. 2010 ACM SIGKDD Conf. on
Knowledge Discovery and Data Mining (KDD'10),
10. Cindy Xide Lin, Bo Zhao, Qiaozhu Mei, and Jiawei Han, “A Statistical Model
for Popular Event Tracking in Social Communities", Proc. 2010 ACM
SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD'10),
11. Chi Wang, Jiawei Han, Yuntao
Jia, Jie Tang, Duo Zhang, Yintao Yu, and Jingyi Guo, “Mining
Advisor-Advisee Relationships from Research Publication Networks",
Proc. 2010 ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD'10),
Washington D.C., July 2010.
Project
Web site URL:
http://www.cs.uiuc.edu/~hanj/projs/eventcube.htm