NSF III-Core-Small: MoveMine: Mining
Sophisticated Patterns and Actionable Knowledge from Massive Moving Object Data
E-mail: hanj
at cs.uiuc.edu, URL: http://www.cs.uiuc.edu/~hanj
List of Supported Students and Staff
§
Zhenhui Li, Ph.D. student, Department of Computer Science,
§
Lu An Tang,
Ph.D. student, Department of Computer Science,
§
Manish Gupta,
Ph.D. student, Department of Computer Science,
Project Summary
This research project is to investigate principles
and methods for uncovering sophisticated patterns and actionable knowledge from
massive moving object data. Thanks to
the rapid progress and broad adoption of sensor, GPS, wireless network, and
other advanced technologies, moving object data have been accumulating in
unprecedented scale. However, moving object data could be dynamic, sparse, scattered, and noisy, and patterns and knowledge
to be mined could be deeply hidden,
sophisticated, and subtle. The MoveMine project investigates effective and scalable methods
for mining various kinds of complex patterns from dynamic and noisy moving
object data, finding multiple interleaved periodic patterns, and performing
in-depth multidimensional analysis of moving object data. It integrates and extends multiple disciplinary
approaches derived from spatiotemporal data analysis, data mining, pattern
recognition, statistics, and machine learning.
The study takes bird and animal movement data and traffic data as the
major sources of data for investigation.
However, developed methods can be applied to the analysis of many other
kinds of moving object data for environmental study, traffic control, law
enforcement, and protection of homeland security. The study also addresses the issue of
ensuring privacy and security protection while developing powerful pattern and
knowledge discovery mechanisms. 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/movemine.htm).
Publications and Products: (Note: major publications
related to this project are in bold font)
Books (authored or edited)
1. Jiawei Han, Micheline Kamber, and Jian Pei, Data
Mining: Concepts and Techniques, 3rd ed., Morgan Kaufmann, 2011.
2.
Ashok N. Srivastava and Jiawei Han (eds.), Machine Learning and Knowledge Discovery
for Engineering Systems Health Management: Detection, Diagnostics, and
Prognostics, Chapman & Hall, 2011.
3.
David Lo, Siau-Cheng Khoo, Jiawei Han, and Chao Liu
(eds.), Mining Software Specifications: Methodologies and Applications, Taylor
& Francis, 2011.
4.
Philip S. Yu, Jiawei Han
and Christos Faloutsos (eds.), Link Mining: Models,
Algorithms and Applications, Springer, 2010 (586 + xxiii pages).
Journal articles (including accepted)
1. Mohammad Mehedy
Masud, Clay Woolam, Jing Gao, Latifur Khan, Jiawei Han, Kevin W. Hamlen, and Nikunj C. Oza, Facing the Reality of Data Stream Classification:
Coping with Scarcity of Labeled
Data, Knowledge and Information Systems (KAIS), accepted June 2011.
2.
Zhenhui
Li, Jiawei Han, Bolin Ding, and Roland Kays, Mining
Periodic Behaviors of Object Movements
for Animal and Biological Sustainability Studies, Data Mining and
Knowledge Discovery, accepted June 2011.
3. Liangliang Cao, Xin
Jin, Zhijun Yin, Andrey Del
Pozo, Jiebo Luo, Jiawei Han, Thomas S. Huang,
RankCompete: Simultaneous Ranking and Clustering of
Information Networks, Neurocomputing (special
issue on Learning from Social Media
Network), conditionally accepted 5/22/11.
4.
Lijun Zhang, Chun Chen, Jiajun
Bu, Deng Cai, and Jiawei Han, Locally Discriminative Co-Clustering, IEEE
Transactions on Knowledge and Data Engineering (TKDE), accepted 2/15/11.
5.
Bolin Ding, Bo Zhao, Cindy Xide
Lin, Jiawei Han, Chengxiang
Zhai, Ashok Srivastava, Nikunj C. Oza, Efficient
Keyword-Based Search for Top-K Cells in Text Cube", IEEE Transactions on Knowledge
and Data Engineering (TKDE) (Special Issue: Keyword Search on Structured Data),
accepted, Dec. 2010.
6.
Jie Yu, Xin Jin, Jiawei Han, Jiebo Luo, Collection-based
Sparse Label Propagation and Its Application on Social Group Suggestion from
Photos", ACM Transactions on Intelligent Systems and Technology (TIST),
2(2), 2011
7. Zhenhui Li, Jiawei Han, Ming Ji, Lu-An Tang, Yintao Yu, Bolin
Ding, Jae-Gil Lee, and Roland Kays, MoveMine: Mining Moving Object Data for Discovery of Animal
Movement Patterns", ACM Transactions on Intelligent Systems and Technology
(ACM TIST) (Special Issue on Computational Sustainability), accepted Aug. 2010.
8.
Lu Liu, Feida Zhu, Meng Jiang, Jiawei Han, Lifeng Sun, and Shiqiang Yang,
Mining diversity on social media networks", Multimedia Tools and
Applications, accepted 2010.
9.
Mohammad M. Masud, Jing Gao, Latifur Khan, Jiawei Han, and Bhavani Thuraisingham, Classification and Novel Class Detection in
Concept-Drifting Data Streams under Time Constraints", IEEE Transactions
on Knowledge and Data Engineering, accepted Feb. 2010.
10. 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, 23(5):713-725, 2011.
11. Xin Jin, Sangkyum Kim, Jiawei Han, Liangliang Cao, and Zhijun Yin, A General Framework for Efficient Clustering
of Large Datasets Based on Activity Detection", Statistical Analysis and
Data Mining, 4(1): 11-29, 2011.
12. Hongyan Liu, Yuan Lin, and Jiawei
Han, Methods for Mining Frequent Items in Data Streams: An Overview",
Knowledge and Information Systems, 26(1): 1-30, 2011.
13. Deng Cai, Xiaofei
He, and Jiawei Han, Speed up Kernel Discriminant
Analysis", VLDB Journal, 20(1): 21-33, 2011.
14. Tim Weninger, Fabio Fumarola, Rick
Barber, Jiawei Han, Donato Malerba, Unexpected Results in Automatic List Extraction
on the Web, SIGKDD Explorations, 12(2): 26-30, 2010.
15. Zhenhui Li, Bolin Ding, Jiawei
Han, and Roland Kays, Swarm: Mining Relaxed Temporal
Moving Object Clusters", PVLDB 3(1): 723-734, 2010. (Also, Proc. 2010 Int.
Conf. on Very Large Data Bases (VLDB'10), Singapore, Sept. 2010.)
16. Peixiang Zhao and Jiawei Han, On
Graph Query Optimization in Large Networks", PVLDB 3(1): 340-351, 2010.
(Also, Proc. 2010 Int. Conf. on Very Large Data Bases (VLDB'10), Singapore,
Sept. 2010.)
17. Marisa Thoma, Hong Cheng, Arthur Gretton,
Jiawei Han, Hans-Peter Kriegel,
Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan and Karsten M. Borgwardt, Discriminative Frequent Subgraph
Mining with Optimality Guarantees", Statistical Analysis and Data Mining,
3(5):302-318, 2010.
18. Manish
Gupta, Rui Li, Zhijun Yin,
and Jiawei Han, Survey on Social Tagging
Techniques", SIGKDD Explorations, 12(1):58-72, 2010.
19. 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.
20. TianyiWu, Yuguo Chen, and Jiawei Han, Re-Examination of Interestingness Measures in
Pattern Mining: A Unified Framework", Data Mining and Knowledge Discovery,
21(3):371-397, 2010.
Book
Chapters
1. Manish Gupta, Rui
Li, Zhijun Yin, and Jiawei
Han, An Overview of Social Tagging Techniques", in Charu
C. Aggarwal (ed.), Social Network Data Analysis, pp.
447-498, Springer, 2011.
2. Xiaoxin Yin, Jiawei
Han, and Philip S. Yu, Scalable Link-Based Similarity Computation and
Clustering", in Philip S. Yu, Jiawei Han and
Christos Faloutsos (eds.), Link Mining: Models,
Algorithms and Applications, Springer, 2010, pp. 45-72.
3. Hong Cheng, Xifeng
Yan and Jiawei Han, Discriminative Frequent
Pattern-Based Graph Classification", in Philip S. Yu, Jiawei
Han and Christos Faloutsos (eds.), Link Mining:
Models, Algorithms and Applications, Springer, 2010, pp. 237-264.
4. Xiaoxin Yin, Jiawei
Han, and Philip S. Yu, Veracity Analysis and Object Distinction", in
Philip S. Yu, Jiawei Han and Christos Faloutsos (eds.), Link Mining: Models, Algorithms and Applications,
Springer, 2010, pp. 283-306.
5. Chen Chen,
Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, and Raghu Ramakrishnan,
InfoNetOLAP: OLAP and Mining of Information
Networks", in Philip S. Yu, Jiawei Han and
Christos Faloutsos (eds.), Link Mining: Models,
Algorithms and Applications, Springer, 2010, pp. 411-438.
6. Yizhou Sun and Jiawei
Han, Integrating Clustering and Ranking for Heterogeneous Information Network
Analysis", in Philip S. Yu, Jiawei Han and
Christos Faloutsos (eds.), Link Mining: Models,
Algorithms and Applications, Springer, 2010, pp. 439-474.
7. Chen Chen,
Cindy Xide Lin, Matt Fredrikson,
Mihai Christodorescu, Xifeng Yan, and Jiawei Han,
Mining Large Information Network by Graph Summarization", in Philip S.
Yu, Jiawei Han and Christos Faloutsos
(eds.), Link Mining: Models, Algorithms and Applications, Springer, 2010, pp.
475-504.
8. 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.
9. Haixun Wang, Philip S. Yu, Jiawei Han, Mining Concept-Drifting Data Streams", in
Oded Maimon and Lior Rokach (Eds.), Data Mining
and Knowledge Discovery Handbook, 2nd ed., Springer 2010 pp. 789-802.
Refereed Conference Publications
1.
Quanquan Gu,
Zhenhui Li, and Jiawei Han,
Linear Discriminant Dimensionality
Reduction, Proc. 2011 European Conf. on
Machine Learning and Principles and Practice of Knowledge Discovery in
Databases (ECMLPKDD'11), Athens, Greece, Sept. 2011
2.
Sangkyum Kim, Marina Barsky, and Jiawei Han, Efficient Mining of Top Correlated
Patterns Based on Null-Invariant Measures,
Proc. 2011 European Conf. on Machine Learning and Principles and Practice of
Knowledge Discovery in Databases (ECMLPKDD'11), Athens, Greece, Sept. 2011
3.
Quanquan Gu, Zhenhui
Li, and Jiawei Han, Generalized
Fisher Score for Feature Selection, Proc. of
2011 Int. Conf. on Uncertainty in Artificial Intelligence (UAI'11),
Barcelona, Spain, July 2011.
4.
Hongbo Deng, Jiawei Han, Bo Zhao, Yintao Yu, Cindy Xide Lin, "Probabilistic
Topic Models with Biased Propagation on Heterogeneous Information Networks", Proc. of 2011 ACM SIGKDD Int. Conf. on Knowledge
Discovery and Data Mining (KDD'11), San Diego, Aug. 2011.
5.
Ming Ji
and Jiawei Han, "Ranking-Based
Classification of Heterogeneous Information Networks",
Proc. of 2011 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining
(KDD'11), San Diego, Aug. 2011.
6.
Xin Jin, Chi Wang, Jiebo Luo and Jiawei Han, "LikeMiner: A System for Mining the Power of
Like in Social Media Networks", Proc. of 2011
ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'11) (system
demo), San Diego, Aug. 2011.
7.
Manish Gupta, Charu C. Aggarwal, and Jiawei Han, Finding Top-k Shortest Path Distance
Changes in an Evolutionary Network, Proc. of 2011
Int. Symp. on Spatial and
Temporal Databases (SSTD'11), Minneapolis, MN, Aug. 2011.
8. Zhenhui Li, Cindy Xide Lin, Bolin Ding, and Jiawei
Han, Mining
Significant Time Intervals for Relationship Detection,
Proc. of 2011 Int. Symp. on
Spatial and Temporal Databases (SSTD'11), Minneapolis, MN, Aug. 2011.
9. Lu-An Tang, Yu Zheng, Xing Xie, Jing Yuan, Xiao
Yu, Jiawei Han, Retrieving k-Nearest Neighboring
Trajectories by a Set of Point Locations, Proc. of
2011 Int. Symp. on Spatial
and Temporal Databases (SSTD'11), Minneapolis, MN, Aug. 2011.
10.
Quanquan Gu, Zhenhui
Li, and Jiawei Han, "Learning
a Kernel for Multi-Task Clustering", Proc. of
2011 AAAI Conf. on Artificial Intelligence (AAAI'11), San Francisco, CA, Aug.
2011.
11. Yizhou Sun, Jiawei Han, Xifeng Yan, Philip S.
Yu, and Tianyi Wu, PathSim: Meta Path-Based Top-K Similarity
Search in Heterogeneous Information Networks, Proc.
of 2011 Int. Conf. on Very Large Data Bases (VLDB'11), Seattle, WA, Aug. 2011.
12. Feida Zhu, Qiang Qu, David Lo, Xifeng Yan, Jiawei Han, and
Philip S. Yu, Mining
Top-K Large Structural Patterns in a Massive Network,
Proc. of 2011 Int. Conf. on Very Large Data Bases (VLDB'11), Seattle, WA, Aug.
2011.
13. Liwen Sun, Reynold Cheng, Xiang Li, David W. Cheung, and Jiawei Han, On
Link-Based Similarity Join, Proc. of 2011 Int. Conf.
on Very Large Data Bases (VLDB'11), Seattle, WA, Aug. 2011.
14. Manish Gupta, Charu Aggarwal, Jiawei Han and Yizhou Sun, "Evolutionary Clustering and Analysis
of Bibliographic Networks", Proc. of 2011 Int.
Conf. on Advances in Social Network Analysis and Mining (ASONAM'11), Kaohsiung,
Taiwan, July 2011.
15. Yizhou Sun, Rick Barber,
Manish Gupta, Charu Aggarwal
and Jiawei Han, "Co-Author Relationship Prediction in
Heterogeneous Bibliographic Networks", Proc. of
2011 Int. Conf. on Advances in Social Network Analysis and Mining (ASONAM'11),
Kaohsiung, Taiwan, July 2011.
16.
Xiao Yu, Ang Pan, Lu-An Tang, Zhenhui Li
and Jiawei Han, "Geo-Friends
Recommendation in GPS-based Cyber-Physical Social Network", Proc. of 2011 Int. Conf. on Advances in Social
Network Analysis and Mining (ASONAM'11), Kaohsiung, Taiwan, July 2011.
17. Hongbo Deng, Jiawei Han, Bo Zhao, "Collective Topic Modeling for
Heterogeneous Networks", Proc. of 2011 Int. ACM
SIGIR Conf. on Research & Development in Information Retrieval (SIGIR'11),
Beijing, China, July 2011. (poster paper)
18. Ming Ji,
Jun Yan, Xiaofei He, Jiawei
Han, Siyu Gu, "Learning Search Tasks in Queries and
Web Pages via Graph Regularization", Proc. of
2011 Int. ACM SIGIR Conf. on Research & Development in Information
Retrieval (SIGIR'11), Beijing, China, July 2011.
19. Sangkyum Kim, Hyungsul Kim, Jiawei Han, Tim Weninger, Hyun Duk Kim, "Authorship Classification: A
Discriminative Syntactic Tree Mining Approach",
Proc. of 2011 Int. ACM SIGIR Conf. on Research & Development in Information
Retrieval (SIGIR'11), Beijing, China, July 2011.
20. Chi Wang, Jiawei Han, Rajat Raina, David Fong, Ding Zhou, "Learning Relevance in a Heterogeneous
Social Network and Its Application in Online Targeting",
Proc. of 2011 Int. ACM SIGIR Conf. on Research & Development in Information
Retrieval (SIGIR'11), Beijing, China, July 2011.
21. Quanquan Gu, Zhenhui Li and Jiawei Han, Joint
Feature Selection and Subspace Learning, Proc. of
2011 Int. Joint Conf. on Artificial Intelligence (IJCAI'11), Barcelona, Spain,
July 2011.
22. Quanquan Gu, Chris Ding and Jiawei
Han, On
Trivial Solution and Scale Transfer Problems in Graph Regularized NMF", Proc. of 2011 Int. Joint Conf. on Artificial
Intelligence (IJCAI'11), Barcelona, Spain, July 2011.
23. Peixiang Zhao, Xiaolei Li, Dong Xin, and Jiawei Han, Graph
Cube: On Warehousing and OLAP Multidimensional Networks,
Proc. of 2011 ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'11), Athens,
Greece, June 2011
24. Bolin Ding, Marianne Winslett, Jiawei Han, and Zhenhui Li, Differentially
Private Data Cube: Optimizing Noise Source and Consistency, Proc. of 2011 ACM SIGMOD Int. Conf. on Management of
Data (SIGMOD'11), Athens, Greece, June 2011
25. Tim Weninger,
Marina Danilevsky, Fabio Fumarola,
Joshua Hailpern, Jiawei
Han, Ming Ji, Thomas J. Johnston, Surya Kallumadi, Hyungsul Kim, Zhijin Li, David McCloskey, Yizhou
Sun, Nathan E. TeGrotenhuis, Chi Wang, and Xiao Yu, WinaCS: Construction and Analysis of
Web-Based Computer Science Information Networks",
Proc. of 2011 ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'11), (system
demo paper), Athens, Greece, June 2011.
26.
Zhijun Yin, Liangliang Cao, Jiawei Han, Jiebo Luo, and Thomas Huang, Diversified
Trajectory Pattern Ranking in Geo-tagged Social Media,
Proc. of 2011 SIAM Conf. on Data Mining (SDM'11), Phoenix, AZ, Apr. 2011.
27.
Zhijun Yin, Liangliang Cao, Jiawei Han, Chengxiang Zhai, and Thomas Huang, Geographical
Topic Discovery and Comparison, Proc. of 2011 Int.
World Wide Web Conf. (WWW'11), Hyderabad, India, Mar. 2011 (Full paper).
28. Tim Weninger,
Fabio Fumarola, Cindy Xide
Lin, Rick Barber, Jiawei Han, and Donato
Malerba, Growing Parallel Paths for
Entity-Page Discovery, Proc. of 2011 Int. World Wide
Web Conf. (WWW'11), Hyderabad, India, Mar. 2011 (Poster paper)
29. Manish Gupta, Yizhou Sun, and Jiawei Han, Trust Analysis with Clustering", Proc. of 2011 Int. World Wide Web Conf. (WWW'11),
Hyderabad, India, March 2011 (Poster paper)
30. Heli Sun, Jianbin Huang, Jiawei Han, Hongbo Deng, Peixiang Zhao, and Boqin Feng, gSkeleton-Clu: Density-based Network Clustering
via Structure-Connected Tree Division or Agglomeration,
Proc. of 2010 Int. Conf. on Data Mining (ICDM'10), Sydney, Australia, Dec. 2010
31. Lu-An Tang, Xiao Yu, Sangkyum Kim, Jiawei Han, Chih-Chieh Hung, and Wen-Chih Peng, Tru-Alarm:
Trustworthiness Analysis of Sensor Networks in Cyber-Physical Systems, Proc. of 2010 Int. Conf. on Data Mining (ICDM'10), Sydney,
Australia, Dec. 2010
32. Jianbin Huang, Heli Sun, Jiawei Han, Hongbo Deng, Yizhou Sun, and Yaguang Liu, SHRINK:
A Structural Clustering Algorithm for Detecting Hierarchical Communities in
Networks", Proc. 2010 ACM Int. Conf. on
Information and Knowledge Management (CIKM'10), Toronto, Canada, Oct. 2010.
33. Lu Liu, Jie Tang, Jiawei Han, Meng Jiang, Shiqiang Yang, Mining Topic-Level Influence in
Heterogeneous Networks", Proc. 2010 ACM
Int. Conf. on Information and Knowledge Management (CIKM'10), Toronto, Canada,
Oct. 2010
34. Xin Jin, Andrew Gallagher, Liangliang Cao, Jiebo Luo, and Jiawei Han, The Wisdom of Social Multimedia:
Using Flickr for Prediction and Forecast", Proc.
2010 ACM Multimedia Int. Conf. (ACM-Multimedia10), Florence, Italy, Oct. 2010
35. Ming Ji,
Yizhou Sun, Marina Danilevsky,
Jiawei Han, and Jing Gao, 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), Barcelona, Spain, Sept. 2010
36. 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
Project Impact
§
Education: Parts of the new research
results are used in Data Mining courses (CS412, CS512) for both undergraduate
and graduate students being taught in the Department of Computer
Science, the
§
Collaborations: For this project we have established collaborations with Boeing, ARL,
NASA, HP Labs,
Current and Future Activities
The
following are some of the highlights of our ongoing work. Please refer to the section: Publications and
Products section for related references.
1.
Study object movement mining in the context of
cyber-physical networks
2.
Study efficient methods for mining more
sophisticated movement patterns than the state-of-the-art
3.
Study methods for anomaly detection for moving
objects in sensor network environment
Area Background
This
project is based on the previous research on data mining, spatiotemporal
data analysis, and data cube and multidimensional analysis.
There have been many research papers published on these themes.
Several textbooks on data mining,
information retrieval and information network analysis provide good
overviews of the principles and algorithms, including (Han and Kamber, 2006, (Hastie, Tibshirani,
and Friedman, 2ed., 2009) and (Miller and Han 2009).
Area References
Potential Related Projects
Project Web
site URL: http://www.cs.uiuc.edu/~hanj/projs/movemine.htm
Online
software: Online software can be downloaded at http://illimine.cs.uiuc.edu,
and online system demo is at http://dm.cs.uiuc.edu/movemine
Online
resources: Research publications
related to this project can be downloaded at Selected
Publications