NSF III-Core-Small: MoveMine: Mining Sophisticated Patterns and Actionable Knowledge from Massive Moving Object Data

National Science Foundation Award Number: NSF IIS 10-17362 (09/01/2010-08/31/2013)

 

 

Contact Information

 

Jiawei Han,  PI
Department of Computer Science
University of Illinois, Urbana-Champaign
1304 West Springfield Ave. , Urbana, Illinois 61801 U.S.A.
Office: (217) 333-6903,   Fax: (217) 265-6494

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, University of Illinois at Urbana-Champaign

§  Lu An Tang, Ph.D. student, Department of Computer Science, University of Illinois at Urbana-Champaign

§  Manish Gupta, Ph.D. student, Department of Computer Science, University of Illinois at Urbana-Champaign

Project Award Information

§  Award Number: NSF IIS 10-17362 (09/01/2010-08/31/2013)

§  Duration: NSF IIS 10-17362 (09/01/2010-08/31/2013)

§  Title: NSF III-Core-Small: MoveMine: Mining Sophisticated Patterns and Actionable Knowledge from Massive Moving Object Data

§  Keywords:  Moving object data mining; multidimensional data analysis; pattern discovery; spatiotemporal data analysis; traffic mining; efficiency and scalability

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.      Lu-An Tang, Xiao Yu, Sangkyum Kim, Quanquan Gu, Jiawei Han, Alice Leung, Thomas La Porta, “Trustworthiness Analysis of Sensor Data in Cyber-Physical Systems”, accepted by Special Issue on Data Warehousing and Knowledge Discovery from Sensors and Streams, Journal of Computer and System Sciences (JCSS), April 2012.

2.      Lu-An Tang, Xiao Yu, Sangkyum Kim, Jiawei Han, Wen-Chih Peng, Yizhou Sun, Alice Leung, Thomas La Porta, “Multidimensional Sensor Data Analysis in Cyber-Physical Systems: An Atypical Cube Approach”, International Journal of Distributed Sensor Networks, Vol. 2012, 2012

3.      Zhijun Yin, Liangliang Cao, Quanquan Gu, and Jiawei Han, “A Probabilistic Model of Community-Based Latent Topic Analysis”, ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2012.

4.      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, 24(2):355-386, 2012.

5.      Lu Liu, Feida Zhu, Meng Jiang, Jiawei Han, Lifeng Sun, and Shiqiang Yang, “Mining diversity on social media networks”, Multimedia Tools and Applications, 56(1): 179-205 (2012)

6.      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), 2(4):37, 2011.

7.      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.

8.      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.

9.      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.

10.  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.

11.  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):12, 2011

12.  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), 2(4):37, 2011.

13.  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.

14.  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.

15.  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.

16.  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.

17.  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.

18.  Deng Cai, Xiaofei He, and Jiawei Han, “Speed up Kernel Discriminant Analysis", VLDB Journal, 20(1): 21-33, 2011.

19.  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.

20.  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.)

21.  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.)

22.  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.

23.  Manish Gupta, Rui Li, Zhijun Yin, and Jiawei Han, “Survey on Social Tagging Techniques", SIGKDD Explorations, 12(1):58-72, 2010.

24.  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.

25.  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.      Zhenhui Li, Jingjing Wang, and Jiawei Han, "Mining Periodicity for Sparse and Incomplete Event Data", Proc. of 2012 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'12), Beijing, China, Aug. 2012

2.      Jingjing Wang and Bhaskar Prabhala, "Periodicity Based Next Place Prediction", Proc. of Workshop on Mobile Data Challenge by Nokia, Newcastle, UK, June 2012

3.      Liangliang Cao, John Smith, Zhen Wen, Zhijun Yin, Xin Jin, and Jiawei Han, "BlueFinder: Estimate Where a Beach Photo Was Taken" (poster paper), Proc. of 2012 Int. Conf. on Word Wide Web (WWW'12), Lyon, France, Apr. 2012.

4.      Manish Gupta, Peixiang Zhao, and Jiawei Han, "Evaluating Event Credibility on Twitter", Proc. 2012 SIAM Int. Conf. on Data Mining (SDM'12), Anaheim, CA, April 2012.

5.      Quanquan Gu, Marina Danilevsky, Zhenhui Li, and Jiawei Han, “Locality Preserving Feature Learning”, Proc. 2012 Int. Conf. on Artificial Intelligence and Statistics (AISTAT'12), La Palma, Canary Islands, April 2012.

6.      Lu-An Tang, Yu Zheng, Jing Yuan, Jiawei Han, Alice Leung, Chih-Chieh Hung, and Wen-Chih Peng, "On Discovery of Traveling Companions from Streaming Trajectories", Proc. 2012 IEEE Int. Conf. on Data Engineering (ICDE'12), Arlington, VA, Apr. 2012.

7.      Lu-An Tang, Xiao Yu, Sangkyum Kim, Jiawei Han, Yizhou Sun, Wen-Chih Peng, Hector Gonzalez, Sebastian Seith, "Multidimensional Analysis of Atypical Events in Cyber-Physical Data", Proc. 2012 IEEE Int. Conf. on Data Engineering (ICDE'12), Arlington, VA, Apr. 2012.

8.      Zhijun Yin, Liangliang Cao, Jiawei Han, Chengxiang Zhai, and Thomas Huang, "LPTA: A Probabilistic Model for Latent Periodic Topic Analysis", Proc. 2011 IEEE Int. Conf. on Data Mining (ICDM'11), Vancouver, Canada, Dec. 2011.

9.      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.

10.  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

11.  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

12.  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.

13.  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.

14.  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.

15.  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.

16.  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.

17.  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.

18.  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.

19.  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.

20.  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.

21.  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.

22.  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.

23.  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.

24.  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.

25.  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.

26.  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) 

27.  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.

28.  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.

29.  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.

30.  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.

31.  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.

32.  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

33.  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

34.  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.

35.  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.

36.  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).

37.  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)

38.  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)

39.  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

40.  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

41.  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.

42.  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

43.  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-Multimedia’10), Florence, Italy, Oct. 2010

44.  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

45.  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 University of Illinois at Urbana-Champaign.    Moreover, the research results have been and will continuously be published timely in international conferences and journals and be distributed world-wide for education and research.  The new progress will also be integrated into the new edition of our data mining textbook and other research collections.

§  Collaborations: For this project we have established collaborations with Boeing, ARL, NASA, HP Labs, IBM T.J. Watson Research Center, Yahoo! Research, Microsoft Research, and NCSA (National Center of Supercomputer Applications).  Through such collaborations we expect to have access to real datasets and applications and produce more research results.

 

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

·         Ralf Hartmut Güting and Markus Schneider, Moving objects databases, Morgan Kaufmann, 2005.

·         Jiawei Han, Micheline Kamber, and Jian Pei, Data Mining: Concepts and Techniques, 3rd edition, Morgan Kaufmann, 2011.

·         Hillol Kargupta, Jiawei Han, Philip Yu, Rajeev Motwani, and Vipin Kumar (eds.), Next Generation of Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series), Taylor & Francis, 2008.

·         Harvey Miller and Jiawei Han (eds.), Geographical Data Mining and Knowledge Discovery, 2nd edition, Taylor & Francis, 2009.

·         Philip S. Yu, Jiawei Han, and Christos Faloutsos (eds), Link Mining: Models, Algorithms, and Applications, Springer, 2010.

 

Potential Related Projects

·         Information Network Analysis and Discovery (Information Network Academic Research Center: Network Science-Collaborative Technology Alliance) (NSF IIS Infonet Project)

·         Knowledge Discovery in Cyberphysical Systems (NSF/CPS)

·         Sequential and Structured Pattern Discovery: Classification, Clustering and Outlier Analysis

·         Discovery of the Dynamics of Data Streams in Multi-Dimensional Space

·         Multidimensional Analysis and Ranking in Databases, Web, and Other Information Repositories

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