Selected Publications Since 2000
· Selected Publications Since 2000
· Selected Publications Before 2000
2010
1.
Dustin Bortner
and Jiawei Han, "Progressive
Clustering of Networks Using Structure-Connected Order of Traversal",
Proc. 2010 Int. Conf. on Data Engineering (ICDE'10),
2.
Bolin Ding, Bo Zhao, Cindy Xide Lin, Jiawei Han, Chengxiang Zhai, "TopCells: Keyword-Based Search of Top-k Aggregated
Documents in Text Cube", Proc. 2010 Int. Conf. on Data Engineering
(ICDE'10), Long Beach, CA, March 2010 .
3.
Xifeng Yan, Bin He, Feida
Zhu, Jiawei Han, "Top-K Aggregation
Queries Over Large Networks", Proc. 2010 Int. Conf. on Data
Engineering (ICDE'10), Long Beach, CA, March 2010.
2009
1.
Yizhou Sun, Jiawei Han,
Jing Gao, and Yintao Yu, iTopicModel: Information Network-Integrated Topic Modeling", Proc. 2009 Int. Conf.
on Data Mining (ICDM'09),
2.
Xiao Yu, Lu An Tang, and Jiawei Han, Filtering
and Refinement: A Two-Stage Approach for Efficient and Effective Anomaly
Detection",
Proc. 2009
Int. Conf. on Data Mining (ICDM'09),
3.
Samson Hauguel, ChengXiang
Zhai, and Jiawei Han, Parallel
PathFinder Algorithms for Mining Structures from
Graphs",
Proc. 2009
Int. Conf. on Data Mining (ICDM'09),
4.
Jing Gao,
Feng Liang, Wei Fan, Yizhou
Sun, and Jiawei Han, Graph-based
Consensus Maximization among Multiple Supervised and Unsupervised Models",
Proc. NIPS 2009 Neural Info. Processing Systems Conf. (NIPS'09),
5.
Peixiang Zhao, Jiawei Han, Yizhou Sun, P-Rank: A
Comprehensive Structural Similarity Measure over Information Networks", Proc. 2009 ACM Conf.
on Information and Knowledge Management (CIKM'09),
6.
Tianyi Wu and Jiawei Han, Subspace Discovery
for Promotion: A Cell Clustering Approach", Proc.
12th Int. Conf. on Discovery Science (DS'09),
7.
Min-Soo Kim and Jiawei Han, CHRONICLE: A Two-Stage Density-based
Clustering Algorithm for Dynamic Networks",
Proc. 12th Int. Conf. on Discovery Science
(DS'09), Porto, Portugal, Oct. 2009.
8.
Jiawei Han, Mining Heterogeneous
Information Networks by Exploring the Power of Links", Proc. 12th Int. Conf. on Discovery Science (DS'09),
9.
Chandrasekar Ramachandran, Rahul Malik, Xin Jin, Jing Gao, Klara
Nahrstedt, and Jiawei Han, VideoMule: A Consensus Learning Approach to
Multi-Label Classification from Noisy User-Generated Videos",
Proc. 2009
ACM Int. Conf. on Multimedia (ACM-MM'09),
10.
Mohammad
M. Masud, Jing Gao, Latifur Khan, Jiawei Han, and Bhavani Thuraisingham, Integrating Novel Class Detection with
Classification for Concept-Drifting Data Streams", Proc. 2009
European Conf. on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases (ECMLPKDD'09),
Bled, Slovenia, Sept. 2009.
11. Min-Soo Kim and Jiawei Han, "A Particle-and-Density Based Evolutionary
Clustering Method for Dynamic Networks", Proc. 2009 Int. Conf.
on Very Large Data Bases (VLDB'09), Lyon, France, Aug. 2009.
12. Tianyi Wu, Dong Xin, Qiaozhu Mei, and Jiawei Han,
"Promotion Analysis in
Multi-Dimensional Space", Proc. 2009 Int. Conf. on Very
Large Data Bases (VLDB'09), Lyon, France, Aug. 2009.
13. Chen Chen, Cindy Lin,
Matt Fredrikson, Mihai Christodorescu, Xifeng Yan, and Jiawei Han, "Mining Graph Patterns Efficiently via
Randomized Summaries", Proc. 2009 Int. Conf. on Very Large Data
Bases (VLDB'09), Lyon, France, Aug. 2009.
14. Yintao Yu, Cindy X. Lin, Yizhou
Sun, Chen Chen, Jiawei Han,
Binbin Liao, Tianyi Wu, ChengXiang Zhai, Duo Zhang, and
Bo Zhao, iNextCube:
Information Network-Enhanced Text Cube",
Proc. 2009
Int. Conf. on Very Large Data Bases (VLDB'09) (system demo), Lyon, France, Aug. 2009.
15.
David Lo, Hong Cheng, Jiawei
Han, SiauCheng Khoo, and Chengnian Sun, Classification of
Software Behaviors for Failure Detection: A Discriminative Pattern Mining
Approach", Proc. 2009 ACM SIGKDD Int. Conf. on Knowledge Discovery
and Data Mining (KDD'09),
1.
Yizhou Sun, Yintao Yu, and Jiawei
Han, Ranking-Based
Clustering of Heterogeneous Information Networks with Star Network Schema", Proc. 2009 ACM SIGKDD Int. Conf. on
Knowledge Discovery and Data Mining
(KDD'09),
2.
Zhijun Yin, Rui Li, Qiaozhu
Mei, and Jiawei Han, Exploring Social
Tagging Graph for Web Object Classification", Proc. 2009 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'09),
3.
Jing Gao, Wei Fan, Yizhou Sun, and Jiawei Han, Heterogeneous
Source Consensus Learning via Decision Propagation and Negotiation", Proc. 2009 ACM SIGKDD Int. Conf. on
Knowledge Discovery and Data Mining (KDD'09),
4.
Deng Cai, Xiaofei He, Xuanhui Wang, Hujun Bao, Jiawei
Han, Locality
Preserving Nonnegative Matrix Factorization, Proc. 2009 Int. Joint Conf. on Arti_cial
Intelligence (IJCAI-09), Pasadena, CA, July 2009.
5. Mohammad Maifi Hasan Khan, Tarek Abdelzaher, Jiawei Han, and Hossein Ahmadi, Finding Symbolic Bug Patterns in Sensor
Networks", Proc.
2009 IEEE Int. Conf. on Distributed Computing in Sensor Systems (DCOSS '09), Marina Del Rey, CA, June 2009.
6.
Jing Gao, Guofei Jiang, Haifeng Chen, and Jiawei Han, Modeling Probabilistic
Measurement Correlations for Problem Determination in Large-Scale Distributed
Systems, Proc. 2009 Int. Conf. on Distributed Computing Systems
(ICDCS'09), Montreal, Quebec, Canada, June 2009.
7.
Mohammad M Masud, Jing Gao,
Latifur Khan, Jiawei Han,
and Bhavani Thuraisingham,
A
Multi-Partition Multi-Chunk Ensemble Technique to Classify Concept-Drifting
Data Streams, Proc. 2009 Pacific-Asia Conf. on Knowledge Discovery and Data Mining
(PAKDD'09),
8.
Xin Jin, Sangkyum Kim, Jiawei
Han, Liangliang Cao, and Zhijun
Yin, GAD: General
Activity Detection for Fast Clustering on Large Data", Proc. 2009
9.
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, Near-Optimal
Supervised Feature
Selection among Frequent Subgraphs", Proc. 2009 SIAM Int. Conf. on Data Mining
(SDM'09), Sparks, NV, April 2009.
10.
Duo Zhang, Chengxiang
Zhai and Jiawei Han, Topic
Cube: Topic Modeling for OLAP on Multidimensional Text Databases", Proc. 2009
11.
Yizhou Sun, Jiawei Han, Peixiang
Zhao, Zhijun Yin, Hong Cheng, Tianyi
Wu, RankClus: Integrating Clustering with Ranking for
Heterogeneous Information Network Analysis, Proc. 2009 Int. Conf. on
Extending Data Base Technology (EDBT'09), Saint-Petersburg, Russia, Mar. 2009.
12.
Jiawei Han, Xifeng Yan,
and Philip S. Yu, Scalable
OLAP and Mining of Information Networks,
2009 Int. Conf. on Extending Data Base Technology (EDBT'09), Saint-Petersburg,
Russia, Mar. 2009.
13.
Bolin Ding, David Lo, Jiawei
Han, and Siau-Cheng Khoo, Efficient Mining
of Closed Repetitive Gapped Subsequences from a Sequence Database, Proc.
2009 Int. Conf. on Data Engineering (ICDE'09),
14.
Xiaolei Li, Zhenhui Li, Jiawei
Han, and Jae-Gil Lee, Temporal Outlier
Detection in Vehicle Traffic Data, Proc. 2009 Int. Conf. on Data
Engineering (ICDE'09),
15.
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, 2009.
16.
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, 2009.
17. Chen Chen, Xifeng Yan,
Feida Zhu, Jiawei Han, and
Philip S. Yu, "Graph OLAP: A Multi-Dimensional Framework for Graph Data
Analysis", accepted by Knowledge and Information Systems (KAIS), 2009.
18. Hector
Gonzalez, Jiawei Han, Hong Cheng, Xiaolei
Li, Diego Klabjan, and Tianyi
Wu, Modeling Massive RFID Datasets: A Gateway-Based Movement-Graph Approach,
Accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE), 2009.
2008
1.
Chen Chen, Xifeng Yan, Feida
Zhu, Jiawei Han, and Philip S. Yu, "Graph
OLAP: Towards Online Analytical Processing on Graphs", Proc. 2008 Int. Conf. on Data Mining
(ICDM'08),
2.
Deng Cai,
Xiaofei He, Xiaoyun Wu, and
Jiawei Han, Non-negative
Matrix Factorization on Manifold, Proc. 2008 Int.
Conf. on Data Mining (ICDM'08),
3.
Cindy Xide Lin,
Bolin Ding, Jiawei Han, Feida
Zhu, and Bo Zhao, "Text Cube:
Computing IR Measures for Multidimensional Text Database Analysis", Proc. 2008 Int. Conf. on Data Mining
(ICDM'08),
4.
Luiz Mendes, Bolin Ding, and Jiawei Han, "Stream
Sequential Pattern Mining with Precise Error Bounds", Proc. 2008 Int. Conf. on Data Mining
(ICDM'08), Pisa, Italy, Dec. 2008.
5.
Mohammad Masud, Jing Gao, Latifur Khan, Jiawei Han, and Bhavani Thuraisingham, "A Practical
Approach to Classify Evolving Data Streams: Training with Limited Amount of
Labeled Data", Proc.
2008 Int. Conf. on Data Mining (ICDM'08),
6.
Jing Gao, Bolin
Ding, Wei Fan, Jiawei Han, and Philip S. Yu,
Classifying Data Streams with Skewed Class Distribution and Concept Drifts,
IEEE Internet Computing (Special Issue on Data Stream Management), 12(6):
37-49, 2008
7.
Mohammad Maifi Hasan
Khan, Hieu Le, Hossein Ahmadi, Tarek Abdelzaher,
and Jiawei Han, DustMiner: Troubleshooting Interactive Complexity Bugs in
Sensor Networks, Proc. 2008 ACM Int. Conf. on Embedded Networked Sensor
Systems (Sensys'08), Raleigh ,
NC
8.
Chen Chen, Cindy Xide
Lin, Xifeng Yan, and Jiawei Han, On Effective
Presentation of Graph Patterns: A Structural Representative Approach, Proc.
2008 ACM Conf. on Information and Knowledge Management (CIKM'08), Napa Valley , CA
9.
Deng Cai, Qiaozhu
Mei, Jiawei Han, and ChengXiang
Zhai, Modeling Hidden
Topics on Document Manifold, Proc. 2008 ACM Conf. on Information and
Knowledge Management (CIKM'08), Napa Valley, CA, Oct. 2008.
10. Jae-Gil
Lee, Jiawei Han, Xiaolei
Li, and Hector Gonzalez, TraClass: Trajectory Classification Using Hierarchical
Region-Based and Trajectory-Based Clustering, Proc. 2008 Int. Conf. on
Very Large Data Base (VLDB'08), Auckland ,
New Zealand
11. Wei Fan, Kun Zhang, Hong
Cheng, Jing Gao, Xifeng Yan, Jiawei
Han, Philip S. Yu, and Olivier Verscheure, Direct Mining of
Discriminative and Essential Graphical and Itemset
Features via Model-based Search Tree, Proc. 2008 ACM SIGKDD Int. Conf. on
Knowledge Discovery and Data Mining (KDD'08), Las Vegas, NV, Aug. 2008.
12. Jing Gao, Wei Fan, Jing Jiang, and Jiawei Han, Knowledge Transfer via
Multiple Model Local Structure Mapping, Proc. 2008 ACM SIGKDD Int.
Conf. on Knowledge Discovery and Data Mining (KDD'08), Las Vegas, NV, Aug.
2008.
13. Bin Jiang, Jian Pei, Xuemin
Lin, David W. Cheung, and Jiawei Han, Mining Preferences from
Superior and Inferior Examples, Proc. 2008 ACM SIGKDD Int. Conf. on
Knowledge Discovery and Data Mining (KDD'08), Las Vegas, NV, Aug. 2008.
14.
Deng Cai, Xiaofei He,
and Jiawei Han, Sparse
Projections over Graph, Proc. 2008 AAAI Conf. on Artificial Intelligence
(AAAI-08), Chicago, Illinois, July 2008.
15.
Sangkyum Kim, Jaebum
Kim, Younhee Ko, Seung-won Hwang and Jiawei Han, PerRank: Personalized Rank Retrieval with Categorical and
Numerical Attributes, Proc. 2008 Int. Conf. on Web-Age Information
Management (WAIM'08), Zhangjiajie, China, July 2008.
16. Tianyi Wu, Dong Xin, and Jiawei Han, ARCube: Supporting Ranking Aggregate Queries in Partially
Materialized Data Cubes, Proc. 2008
ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'08), Vancouver, BC, Canada,
June 2008.
17. Xifeng Yan, Hong Cheng, Jiawei Han, and Philip S. Yu, Mining
Significant Graph Patterns by Scalable Leap Search, Proc. 2008 ACM SIGMOD Int. Conf. on
Management of Data (SIGMOD'08), Vancouver, BC, Canada, June 2008.
18. Xiaolei Li, Jiawei Han, Zhijun Yin, Jae-Gil Lee, and Yizhou
Sun, Sampling
Cube: A Framework for Statistical OLAP over Sampling Data, Proc. 2008 ACM
SIGMOD Int. Conf. on Management of Data (SIGMOD'08), Vancouver, BC, Canada,
June 2008.
19. Yizhou Sun, Tianyi Wu, Hong
Cheng, Jiawei Han, Xiaoxin
Yin, and Peixiang Zhao, BibNetMiner: Mining Bibliographic Information Networks,
(demo paper), Proc. 2008 ACM SIGMOD Int. Conf. on Management of Data
(SIGMOD'08), Vancouver, BC, Canada, June 2008.
20. Sangkyum Kim, Xin Jin and Jiawei Han, SpaRClus: Spatial Relationship Pattern-Based Hierarchical
Clustering, Proc. 2008
21. Ding Yuan, Kyuhyung Lee, Hong Cheng, Gopal Krishna, Zhenmin Li, Xiao
Ma, Yuanyuan Zhou and Jiawei
Han, CISpan: Comprehensive Incremental Mining Algorithms of
Closed Sequential Patterns for Multi-Versional
Software Mining, Proc. 2008 SIAM
Int. Conf. on Data Mining (SDM'08), Atlanta, GA, April 2008.
22. Deng Cai,
Xiaofei He, and Jiawei Han,
"Training
Linear Discriminant Analysis in Linear Time",
Proc. 2008 Int. Conf. on Data Engineering (ICDE'08),
23. Hong Cheng, Xifeng Yan, Jiawei Han, and Philip S.
Yu, "Direct
Discriminative Pattern Mining for Effective Classification", Proc.
2008 Int. Conf. on Data Engineering (ICDE'08), Cancun, Mexico, April 2008.
24. Jae-Gil Lee, Jiawei Han,
and Xiaolei Li, "Trajectory
Outlier Detection: A Partition-and-Detect Framework", Proc. 2008 Int.
Conf. on Data Engineering (ICDE'08),
25. Dong Xin and Jiawei Han, "P-Cube:
Answering Preference Queries in Multi-Dimensional Space", Proc. 2008
Int. Conf. on Data Engineering (ICDE'08),
26. Xiaoxin Yin, Jiawei Han and Philip S. Yu, "Truth Discovery
with Multiple Conflicting Information Providers on the Web", IEEE
Transactions on Knowledge and Data Engineering, 20(6):796-808, 2008.
27.
Xiaofei He, Deng Cai, Jiawei Han, Learning a Maximum
Margin Subspace for Image Retrieval, IEEE Transactions on Knowledge and
Data Engineering, 20(2):189-201, 2008.
28.
Deng Cai,
Xiaofei He, Jiawei Han, SRDA: An
Efficient Algorithm for Large Scale Discriminant
Analysis, IEEE Transactions on Knowledge and Data Engineering, 20(1):1-12,
2008.
29.
Hong Cheng,
Philip S. Yu, and Jiawei
Han, Approximate Frequent Itemset Mining In the
Presence of Random Noise, O. Maimon and L. Rokach (eds.), Soft Computing for Knowledge Discovery and
Data Mining, Springer, 2008, pp. 363-389.
2007
- Deng Cai, Xiaofei He, Wei Vivian Zhang, and Jiawei
Han, Regularized
Locality Preserving Indexing, Proc. 2007 ACM Int. Conf. on
Information and Knowledge Management (CIKM'07), Lisboa,
Portugal, Nov. 2007.
- Deng Cai, Xiaofei
He, and Jiawei Han, A Unified
Approach for Sparse Subspace Learning, Proc. 2007 Int. Conf. on Data
Mining (ICDM'07), Omaha, NE, Oct. 2007.
- Jing Gao, Wei Fan, and Jiawei Han, On
Appropriate Assumptions to Mine Data Streams: Analysis and Practice,
Proc. 2007 Int. Conf. on Data Mining (ICDM'07),
- Deng Cai, Xiaofei He, and Jiawei Han,
Efficient
Kernel Discriminant Analysis via Spectral
Regression, Proc. 2007 Int. Conf. on Data Mining (ICDM'07),
- Chen Chen, Xifeng
Yan, Feida Zhu, and Jiawei Han, gApprox: Mining Frequent Approximate Patterns from a
Massive Network, Proc. 2007 Int. Conf. on Data Mining (ICDM'07),
- Feida Zhu, Xifeng
Yan, Jiawei Han, and
Philip S. Yu, Efficient
Discovery of Frequent Approximate Sequential Patterns, Proc. 2007
Int. Conf. on Data Mining (ICDM'07),
- Chao Liu, Tao Xie, and Jiawei Han, "Mining for Software
Reliability", ICDM'2007
Conference Tutorial,
- Deng Cai, Xiaofei He, and Jiawei Han,, Spectral
Regression for Efficient Regularized Subspace Learning, Proc. 2007 IEEE Int. Conf. On
Computer Vision (ICCI'07), Rio de Janeiro, Brazil, Oct. 2007.
- Deng Cai, Xiaofei He, and Jiawei Han,, Semi-supervised
Discriminant Analysis,
Proc. 2007 IEEE Int. Conf. on Computer Vision (ICCI'07),
10. Chao Liu,
Xiangyu Zhang, Jiawei Han, Yu Zhang and Bharat K. Bhargava, Failure Indexing: A Dynamic Slicing
Based Approach, in Proc. 2007 IEEE Int. Conf. on Software Maintenance (ICSM'07), Paris, France
11. Deng Cai, Xiaofei He, and Jiawei Han, A Unified
Subspace Learning Framework for Content-Based Image Retrieval, in Proc. 2007
Int. Conf. on ACM Multimedia (ACM-MM'07), Augsburg, Germany, Sept. 2007.
12.
Chen Chen, Xifeng Yan, Philip S. Yu, Jiawei Han, DongQing Zhang, and Xiaohui Gu, Towards Graph
Containment Search and Indexing, in Proc. 2007 Int. Conf. on Very Large
Data Bases (VLDB'07), Vienna, Austria, Sept. 2007.
13.
Hector Gonzalez, Jiawei
Han, Xiaolei Li, Margaret Myslinska,
and John Paul Sondag, Adaptive
Fastest Path Computation on a Road Network: A Traffic Mining Approach, in Proc. 2007 Int. Conf. on Very Large Data Bases (VLDB'07), Vienna , Austria
14.
Xiaolei Li and Jiawei Han, Mining Approximate
Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data, in Proc. 2007 Int. Conf. on Very Large Data Bases (VLDB'07), Vienna,
Austria, Sept. 2007.
15.
Tainyi Wu, Xiaolei Li, Dong Xin, Jiawei Han, Jacob Lee, and Ricardo Redder, DataScope:
Viewing Database Contents in Google Maps' Way, in Proc. 2007 Int. Conf. on Very Large Data Bases (VLDB'07), Vienna,
Austria, Sept. 2007 (system demo).
16. Tianyi Wu, Yuguo
Chen and Jiawei Han, Association Mining
in Large Databases: A Re-Examination of Its Measures,
in Proc. 2007 Int. Conf. on Principles and Practice of Knowledge Discovery in
Databases (PKDD'07), Warsaw ,
Poland
17. Jiawei Han, Xiaoxin
Yin, and Philip S. Yu, Exploring the Power
of Links in Data Mining, Tutorial for Proc. 2007
Int. Conf. on Principles and Practice of Knowledge Discovery in Databases
(PKDD'07), Warsaw, Poland, Sept. 2007.
18. Xiaoxin Yin, Jiawei
Han, and Philip S. Yu, Truth Discovery
with Multiple Conflicting Information Providers on the Web, in Proc. 2007
ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'07), San
Jose, CA, Aug. 2007.
19. Xiaolei Li, Jiawei
Han, Jae-Gil Lee, and Hector Gonzalez, Traffic
Density-based Discovery of Hot Routes in Road Networks, in Proc. 2007 Int.
Symp. on Spatial and
Temporal Databases (SSTD'07), Boston
20. Deng Cai,
Xiaofei He and Jiawei Han, Isometric
Projection, in Proc. 2007 AAAI Conf. on Artificial
Intelligence (AAAI-07), Vancouver , B. C., Canada
21. Wen Jin, Anthony K.H. Tung, Martin Ester,
and Jiawei Han, On Efficient
Processing of Subspace Skyline Queries on High Dimensional Data, in Proc. 2007
Int. Conf. on Scientific and Statistical Database Management (SSDBM'07), Banff , Canada
22. Deng Cai,
Xiaofei He, Yuxiao Hu, Jiawei Han, and Thomas Huang,
Learning a Spatially
Smooth Subspace for Face Recognition, in Proc.
2007 IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'07), Minneapolis , MN
23. Jae-Gil Lee, Jiawei Han,
and Kyu-Young Whang, Trajectory
Clustering: A Partition-and-Group Framework, in Proc. 2007 ACM SIGMOD Int.
Conf. on Management of Data (SIGMOD'07), Beijing, China, June 2007.
24. Dong Xin,
Jiawei Han, and Kevin C.-C. Chang, Progressive
and Selective Merge: Computing Top-K with Ad-hoc Ranking Functions, in Proc. 2007 ACM SIGMOD Int. Conf. on Management of
Data (SIGMOD'07), Beijing, China, June 2007.
25. Feida Zhu, Xifeng Yan, Jiawei Han, and Philip S.
Yu, gPrune: A Constraint Pushing Framework for Graph Pattern
Mining, in Proc. 2007 Pacific-Asia Conf. on Knowledge Discovery and Data
Mining (PAKDD'07), Nanjing, China, May 2007. (Best Student Paper
Award)
26. Jing Gao, Wei Fan, and Jiawei Han, A General
Framework for Mining Concept-Drifting Data Streams with Skewed Distributions,
in Proc. 2007 SIAM Int. Conf. on Data Mining (SDM'07), Minneapolis, MN, April
2007.
27. Xiaolei Li, Jiawei Han, Sangkyum Kim, and Hector Gonzalez, ROAM: Rule- and
Motif-Based Anomaly Detection in Massive Moving Object Data Sets, in Proc.
2007
28.
Hong Cheng, Xifeng Yan,
Jiawei Han, and Chih-Wei
Hsu, Discriminative
Frequent Pattern Analysis for Effective Classification, in Proc. 2007 Int.
Conf. on Data Engineering (ICDE'07), Istanbul, Turkey, April 2007.
29.
Feida Zhu, Xifeng Yan, Jiawei
Han, Philip S. Yu, and Hong Cheng, Mining
Colossal Frequent Patterns by Core Pattern Fusion, in Proc. 2007 Int.
Conf. on Data Engineering (ICDE'07), Istanbul, Turkey, April 2007. (Best Student
Paper Award)
30.
Hector Gonzalez, Jiawei Han, and Xuehua Shen, Cost-conscious
Cleaning of Massive RFID Data Sets, in Proc. 2007 Int. Conf. on Data
Engineering (ICDE'07),
31.
Xiaoxin Yin, Jiawei Han, and Philip S. Yu, Object
Distinction: Distinguishing Objects with Identical Names by Link Analysis,
in Proc. 2007 Int. Conf. on Data Engineering (ICDE'07),
32.
Wen Jin, Martin
Ester, Zengjian Hu, and Jiawei Han, The
Multi-Relational Skyline Operator, in Proc. 2007 Int. Conf. on Data
Engineering (ICDE'07), Istanbul, Turkey, April 2007.
33.
Deng Cai, Xiaofei He, Kun Zhou, Jiawei Han and Hujun Bao, Locality Sensitive
Discriminant Analysis, in Proc. 2007 Int.
Joint Conf. on Artificial Intelligence (IJCAI'07), Hyderabad, India, Jan. 2007.
- Xiaoxin Yin, Jiawei Han,
and Philip S. Yu, CrossClus: User-Guided Multi-Relational Clustering,
Data Mining and Knowledge Discovery, 16(1), 2007. 10.1007/s10618-007-0072-z,
SpringerLink Date: July 05, 2007.
- Jianyong Wang, Jiawei Han,
and Chun Li, Frequent
Closed Sequence Mining without Candidate Maintenance, IEEE
Transactions on Knowledge and Data Engineering, 19(8), 2007.
- Chulyun
Kim, Sangkyum Kim, Russell Dorer,
Dan Xie, Jiawei Han,
and Sheng Zhong, TagSmart: Analysis and
Visualization for Yeast Mutant Fitness Data
Measured by Tag Microarrays, BMC
Bioinformatics, 8:128, April 2007. (http://www.biomedcentral.com/1471-2105/8/128)
- Jiawei Han, Hong Cheng, Dong Xin,
and Xifeng Yan, Frequent
Pattern Mining: Current Status and Future Directions, Data Mining and
Knowledge Discovery, 15(1): 55-86, 2007. (Online version published on
January 27, 2007, DOI 10.1007/s10618-006-0059-1 SpringerLink).
- Dong Xin, Jiawei Han, Xifeng Yan and Hong Cheng,
On Compressing Frequent Patterns, Knowledge and Data Engineering,
(Special issue on Intelligent Data Mining), 60(1): 5-29, 2007.
- Dong Xin, Jiawei Han, Xiaolei Li, Zheng Shao, and Benjamin W. Wah, Computing
Iceberg Cubes by Top-Down and Bottom-Up Integration: The StarCubing Approach, IEEE Transactions on
Knowledge and Data Engineering, 19(1): 111-126, 2007.
2006
1.
Chao Liu, Zeng Lian, and Jiawei Han, How Bayesians
Debug?, in Proc. 2006 Int. Conf. on Data Mining
(ICDM'06),
2.
Hong Cheng, Philip S. Yu, and Jiawei
Han, AC-Close:
Efficiently Mining Approximate Closed Itemsets by
Core Pattern Recovery, in Proc. 2006 Int. Conf. on Data Mining (ICDM'06),
3.
Chao Liu and Jiawei Han, Failure Proximity: A
Fault Localization-Based Approach, in Proc. 14th ACM SIGSOFT Symposium on
the Foundations of Software Engineering (FSE'06),
4. Hector Gonzalez, Jiawei Han, and Xiaolei Li, Mining Compressed Commodity Workflows From Massive RFID Data Sets, in Proc. 2006 Int. Conf. on Information and Knowledge Management (CIKM'06), Arlington, VA, Nov. 2006.
5.
Xiaoxin Yin, Jiawei Han, and Philip Yu, LinkClus: Efficient Clustering via Heterogeneous Semantic
Links, in Proc. 2006 Int. Conf. on Very Large Data Bases (VLDB'06),
6.
Hector Gonzalez, Jiawei Han,
and Xiaolei Li, FlowCube: Constructuing RFID FlowCubes for Multi-Dimensional Analysis of Commodity Flows,
in Proc. 2006 Int. Conf. on Very Large Data Bases (VLDB'06),
7.
Dong Xin, Chen Chen, and Jiawei Han, Towards
Robust Indexing for Ranked Queries, in Proc. 2006 Int. Conf. on Very Large
Data Bases (VLDB'06),
8.
Dong Xin, Jiawei
Han, Hong Cheng, and Xiaolei Li, Answering
Top-k Queries with Multi-Dimensional Selections: The Ranking Cube Approach,
in Proc. 2006 Int. Conf. on Very Large Data Bases (VLDB'06),
9. Dong Xin, Hong Cheng, Xifeng Yan, and Jiawei Han, Extracting Redundancy-Aware Top-K Patterns, in Proc. 2006 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'06), Philadelphia, PA, Aug. 2006.
10. Qiaozhu Mei, Dong Xin, Hong Cheng, Jiawei Han, and ChengXiang Zhai, Generating Semantic Annotations for Frequent Patterns with Context Analysis, in Proc. 2006 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'06), Philadelphia, PA, Aug. 2006. (Best Student Paper Runner-Up Award)
11. Chao
Liu, Chen Chen, Jiawei Han,
and Philip Yu, GPLAG:
Detection of Software Plagiarism by Procedure Dependency Graph Analysis,
in Proc. 2006 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining
(KDD'06),
12. Dong Xin, Xuehua Shen, Qiaozhu Mei, and Jiawei Han, Discovering Interesting Patterns Through User's Interactive Feedback, in Proc. 2006 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'06), Philadelphia, PA, Aug. 2006.
13. Deng Cai, Xiaofei He and Jiawei Han, Tensor Space Model for Document Analysis, in Proc. 2006 Int. ACM SIGIR Conf. on Research & Development on Information Retrieval (SIGIR'06), Seattle, WA, Aug. 2006.
14. Jiawei Han, Hector Gonzalez, Xiaolei Li and Diego Klabjan, Warehousing and Mining Massive RFID Data Sets, (Keynote Speech), 2006 Int. Conf. on Advance Data Mining and Its Applications (ADMA06), XiAn, China, Aug. 2006.
15. Hongyan Liu, Ying Lu, Jiawei Han,
and Jun He, Error-Adaptive
and Time-Aware Maintenance of Frequency Counts over Data Streams, in Proc.
2006 Int. Conf. on Web-Age Information Management (WAIM'06),
16. Kaushik Chakrabarti, Venkatesh Ganti, Jiawei Han, and Dong Xin, Ranking Objects Based on Relationships, in Proc. 2006 ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'06), Chicago, IL, June 2006.
17. Xiaolei Li, Jiawei Han, and Sangkyum Kim, Motion-Alert: Automatic Anomaly Detection in Massive Moving Objects, Proc. 2006 IEEE Int. Conf. on Intelligence and Security Informatics (ISI'06), San Diego, CA, May 2006.
18. Wen Jin, Anthony K. H. Tung, Jiawei Han, and Wei Wang, Ranking Outliers Using Symmetric Neighborhood Relationship, in Proc. 2006 Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PAKDD'06), Singapore, April 2006.
19. Hongyan Liu, Jiawei Han, Dong Xin, and Zheng Shao, Mining
Interesting Patterns from Very High Dimensional Data: A Top-Down Row
Enumeration Approach, in Proc. 2006
20. Chao Liu, Xifeng Yan, and Jiawei Han, Mining Control Flow Abnormality for Logic Error Isolation, in Proc. 2006 SIAM Int. Conf. on Data Mining (SDM'06), Bethesda, MD, April 2006.
21. Charu Aggarwal, Chen Chen, and Jiawei Han, On the Inverse
Classification Problem and its Applications, in Proc. 2006 Int. Conf. on
Data Engineering (ICDE'06),
22. Hector
Gonzalez, Jiawei Han, Xiaolei Li,
and Diego Klabjan, Warehousing and
Analysis of Massive RFID Data Sets, in Proc. 2006 Int. Conf. on Data
Engineering (ICDE'06),
23. Hongyan Liu, Jiawei Han, Dong Xin, and Zheng Shao, Top-Down Mining of Interesting Patterns from Very High Dimensional Data, in Proc. 2006 Int. Conf. on Data Engineering (ICDE'06), Atlanta, Georgia, April 2006.
24. Dong
Xin, Jiawei Han, Zheng Shao, and Hongyan Liu, C-Cubing:
Efficient Computation of Closed Cubes by Aggregation-Based Checking, in
Proc. 2006 Int. Conf. on Data Engineering (ICDE'06),
25. Xifeng Yan, Feida Zhu, Jiawei Han, and Philip S. Yu, Searching Substructures with Superimposed Distance, in Proc. 2006 Int. Conf. on Data Engineering (ICDE'06), Atlanta, Georgia, April 2006.
26. Chao Liu, Long Fei, Xifeng Yan, Jiawei Han and Samuel P. Midkiff, Statistical Debugging: A Hypothesis Testing-based Approach, IEEE Transaction on Software Engineering, 32(10): 831-848, 2006.
27. Yixin Chen, Guozhu Dong, Jiawei Han, Jian Pei, Benjamin W.
Wah, and Jianyong Wang, Regression Cubes
with Lossless Compression and Aggregation, IEEE Transactions on Knowledge
and Data Engineering, 18(12): 1585-1599, 2006.
28. Jiangyong Wang, Jiawei Han, and
29. Xiaoxin Yin, Jiawei Han, Jiong Yang and Philip S. Yu, Efficient
Classification across Multiple Database Relations: A CrossMine
Approach, IEEE Transactions on Knowledge and Data Engineering, 18(6):
770-783, 2006.
30. Charu Aggarwal, Jiawei Han, Jianyong Wang, and
Philip S. Yu, A Framework for
On-Demand Classification of Evolving Data Streams, IEEE Transactions
on Knowledge and Data Engineering, 18(5):577-789, 2006.
2005
1.
Deng Cai, Zheng Shao,
Xiaofei He, Xifeng Yan, Jiawei Han, Community
Mining from Multi-Relational Networks, in Proc. 2005 European Conf. on
Principles and Practice of Knowledge Discovery in Databases (PKDD'05), Porto,
Portugal, Oct., 2005.
2.
Wen Jin, Martin Ester
and Jiawei Han, Efficient
Processing of Ranked Queries with Sweeping Selection, in Proc. 2005 European Conf. on Principles
and Practice of Knowledge Discovery in Databases (PKDD'05), Porto, Portugal,
Oct., 2005.
3.
Xiaoxin Yin and Jiawei Han, Efficient
Classification from Multiple Heterogeneous Databases, in Proc. 2005
European Conf. on Principles and Practice of Knowledge Discovery in Databases
(PKDD'05), Porto, Portugal, Oct., 2005.
4.
Chen Chen, Dong Xin, Jiawei Han, Accelerating
DNA Sequencing by Hybridization with Noises, in Proc. 2005 ACM-SIGKDD
Workshop on Data Mining in Bioinformatics (BioKDD'05), Chicago, IL, Aug. 2005.
5.
Deng Cai, Zheng Shao,
Xiaofei He, Xifeng Yan, Jiawei Han, Mining
Hidden Community in Heterogeneous Social Networks, in Proc. 2005 ACM-SIGKDD
Workshop on Link Discovery: Issues, Approaches and Applications (LinkKDD'05),
Chicago, IL, Aug. 2005.
6.
H. Liu, X. Yin,
J. Han, An
Efficient Multi-relational Naοve Bayesian Classifier Based on Semantic
Relationship Graphs, in Proc. 2005 ACM-SIGKDD Workshop on Multi-Relational
Data Mining (KDD/MRDM'05), Chicago, IL, Aug. 2005.
7.
J. Yang, X. Yan, J. Han, and W. Wang, Discovering
Evolutionary Classifier over High Speed Non-Static Stream, in S. Bandyopadhyay et al. (eds.), Advanced Methods for Knowledge Discovery from
Complex Data, Springer Verlag, 2005.
8.
J. Han, J. Pei,
and X. Yan, Sequential Pattern
Mining by Pattern-Growth: Principles and Extensions, in W. W. Chu and T.
Y. Lin (eds.), Recent Advances in Data Mining and Granular Computing
(Mathematical Aspects of Knowledge Discovery), Springer Verlag,
2005.
9.
J. Wang, J.
Han, Y. Lu, and P. Tzvetkov, TFP: An Efficient
Algorithm for Mining Top-K Frequent Closed Itemsets,
IEEE Transactions on Knowledge and Data Engineering, 17(5):652-664, 2005.
10. C. Liu, X. Yan, L. Fei, J. Han, and S. Midkiff, SOBER: Statistical
Model-based Bug Localization, in Proc. 2005 ACM SIGSOFT Symp. on the Foundations of
Software Engineering (FSE 2005),
11. D. Xin, J. Han, X. Yan and H. Cheng, Mining Compressed
Frequent-Pattern Sets, in Proc. 2005 Int. Conf. on Very Large Data Bases
(VLDB'05), Trondheim, Norway, Aug. 2005.
12. X. Yan, H. Cheng, J. Han,
and D. Xin, Summarizing Itemset Patterns: A Profile-Based Approach, in Proc.
2005 Int. Conf. on Knowledge Discovery and Data Mining (KDD'05),
13. X. Yan, X. J. Zhou, and J.
Han, Mining
Closed Relational Graphs with Connectivity Constraints, Proc. 2005 Int.
Conf. on Knowledge Discovery and Data Mining (KDD'05),
14. X. Yin, J. Han, and P.S. Yu, Cross-Relational
Clustering with User's Guidance, in Proc. 2005 Int. Conf. on Knowledge
Discovery and Data Mining (KDD'05), Chicago, IL, Aug. 2005.
15. S. Cong, J. Han, and D.
16. D. Cai and X. He. Orthogonal Locality
Preserving Indexing, in Proc. 2005 Int. Conf. on Research and Development
in Information Retrieval (SIGIR'05), Salvador, Brazil, Aug. 2005.
17. X. Yin, J. Han, and J. Yang, Searching for Related
Objects in Relational Databases, in Proc. 2005 Int. Conf. on Scientific
and Statistical Database Management (SSDBM'05), Santa Barbara, CA, June 2005.
18. H. Hu, X. Yan, Yu, J. Han and X. J. Zhou, Mining Coherent Dense Subgraphs across Massive Biological Networks for Functional
Discovery, in Proc. 2005 Int. Conf. on Intelligent Systems for Molecular
Biology (ISMB 2005), Ann Arbor, MI, June 2005.
19. X. Yan, P. S. Yu, and J.
Han, Substructure
Similarity Search in Graph Databases, in Proc. 2005 ACM-SIGMOD Int. Conf.
on Management of Data (SIGMOD'05), Baltimore, Maryland, June 2005.
20. C. Liu, X. Yan, H. Yu, J.
Han, and P. S. Yu, Mining Behavior
Graphs for Backtrace of Noncrashing
Bugs, in Proc. 2005 SIAM Int. Conf. on Data Mining (SDM'05), Newport
Beach, CA, April 2005.
21. H. Cheng, X. Yan, and J.
Han, SeqIndex: Indexing Sequences by Sequential Pattern Analysis,
in Proc. 2005
22. X. Li, J. Han, X. Yin, and D. Xin,
Mining
Evolving Customer-Product Relationships in Multi-Dimensional Space, in
Proc. 2005 Int. Conf. on Data Engineering (ICDE'05), Tokyo, Japan, April 2005.
23. X. Yan, X. J. Zhou, J.
Han, Mining
Closed Relational Graphs with Connectivity Constraints, in Proc. 2005 Int.
Conf. on Data Engineering (ICDE'05), Tokyo, Japan, April 2005.
24. S. Cong, J. Han and D. Padua, A Sampling-based
Framework for Parallel Data Mining, in Proc. 2005 ACM SIGPLAN Symp. on Principles & Practice
of Parallel Programming (PPOPP'05),
25. J. Yang, X. Yan, J. Han,
and W. Wang, Discovering
Evolutionary Classifier over High Speed Non-static Stream, in S. Bandyopadhyay et al. (eds.), Advanced Methods for Knowledge
Discovery from Complex Data, Springer Verlag, 2005.
26. Hwanjo Yu, Jiong Yang, Jiawei Han, and Xiaolei Li, Making SVM
Scalable to Large Data Sets Using Hierarchical Indexing, Data Mining and
Knowledge Discovery, 11(3): 295-321, 2005.
27. Jiawei Han, Yixin Chen, Guozhu Dong, Jian Pei, Benjamin
W. Wah, Jianyong Wang, and
Y. Dora Cai, Stream Cube: An
Architecture for Multi-Dimensional Analysis of Data Streams, Distributed
and Parallel Databases, 18(2): 173-197, 2005.
28. Xifeng Yan, Philip Yu, and Jiawei Han, Graph Indexing
Based on Discriminative Frequent Structure Analysis, ACM Transactions on
Database Systems, 30(4): 960-993 2005.
29. Deng Cai, Xiaofei He and Jiawei Han, Document
Clustering Using Locality Preserving Indexing, IEEE Transactions on
Knowledge and Data Engineering, 17(12):1624-1637, 2005.
30. C. Aggarwal, J. Han, J.
Wang, and P. S. Yu, On Efficient
Algorithms for High Dimensional Projected Clustering of Data Streams, Data
Mining and Knowledge Discovery, 10:251-272, 2005.
31. Petre Tzvetkov, Xifeng Yan, Jiawei
Han, TSP:
Mining top-k closed sequential patterns, Knowl.
Inf. Syst., 7(4): 438-457, 2005.
32. J. Wang, J. Han, Y. Lu, and P. Tzvetkov,
TFP: An
Efficient Algorithm for Mining Top-K Frequent Closed Itemsets,
IEEE Transactions on Knowledge and Data Engineering, 17(5):652-664, 2005.
33. K. Wang, Y. Jiang, J. X. Yu, G. Dong, and J. Han, Divide-and-Approximate:
A Novel Constraint Push Strategy for Iceberg Cube Mining, IEEE
Transactions on Knowledge and Data Engineering, 17(3):354-368, 2005.
34. Xiaofei He, Deng Cai, Haifeng Liu, Jiawei Han, Image clustering
with tensor representation, ACM Multimedia 2005:132-140
2004
1.
W. Jin, J. Han,
and M. Ester, Mining Thick
Skylines over Large Databases, Proc. 2004 European Conf. on Principles of
Principles and Practice of Knowledge Discovery in Databases (PKDD04), Pisa,
Italy, Sept. 2004.
2.
C. Aggarwal, J.
Han, J. Wang, and P.
S. Yu, A
Framework for Projected Clustering of High Dimensional Data Streams, Proc.
2004 Int. Conf. on Very Large Data Bases (VLDB'04), Toronto, Canada, Aug. 2004.
3.
X. Li, J. Han,
and H. Gonzalez, High-Dimensional
OLAP: A Minimal Cubing Approach, Proc. 2004 Int. Conf. on Very
Large Data Bases (VLDB'04),
4.
C. Aggarwal, J. Han, J. Wang, and P. S. Yu, On Demand
Classification of Data Streams, Proc. 2004 Int. Conf. on Knowledge
Discovery and Data Mining (KDD'04),
5.
H. Cheng, X. Yan, and J.
Han, IncSpan: Incremental
Mining of Sequential Patterns in Large Database, Proc. 2004 Int.
Conf. on Knowledge Discovery and Data Mining (KDD'04),
6.
B. He, K.C.-C.
Chang, and J. Han, Discovering
Complex Matchings across Web Query Interfaces: A
Correlation Mining Approach, Proc.
2004 Int. Conf. on Knowledge Discovery and Data Mining (KDD'04),
7.
Y. Li, J. Han,
and J. Yang, Clustering
Moving Objects, Proc. 2004 Int. Conf. on Knowledge Discovery and Data
Mining (KDD'04), Seattle, WA, Aug. 2004.
8.
A. Wu, M.
Garland, and J. Han, Mining
Scale-Free Networks using Geodesic Clustering, Proc. 2004 Int. Conf. on
Knowledge Discovery and Data Mining (KDD'04),
9.
J. Pei, J. Han,
B. Mortazavi-Asl, J. Wang, H. Pinto, Q. Chen, U. Dayal, and M.-C.
Hsu, Mining
Sequential Patterns by Pattern-Growth: The PrefixSpan
Approach, IEEE Transactions on Knowledge and Data Engineering, 16(10),
2004.
10. J. Han, J. Pei, and X. Yan,
From Sequential
Pattern Mining to Structured Pattern Mining: A Pattern-Growth Approach,
Journal of Computer Science and Technology, 19(3): 257-279, 2004.
11. Z. Shao, J. Han, and D. Xin, MM-Cubing:
Computing Iceberg Cubes by Factorizing the Lattice Space, Proc. 2004 Int.
Conf. on Scientific and Statistical Database Management (SSDBM'04),
12. Y. Li, J. Yang, and J. Han, Continuous
K-Nearest Neighbor Search for Moving Objects, Proc. 2004 Int. Conf. on
Scientific and Statistical Database Management (SSDBM'04), Santorini
Island, Greece, June 2004.
13. J. Han, J. Pei, Y. Yin and R. Mao, Mining Frequent
Patterns without Candidate Generation: A Frequent-Pattern Tree Approach,
Data Mining and Knowledge Discovery, 8(1):53-87, 2004.
14. X. Yan, P. S. Yu, and J.
Han, Graph
Indexing: A Frequent Structure-based Approach, Proc. 2004 ACM-SIGMOD Int.
Conf. on Management of Data (SIGMOD'04), Paris, France, June 2004.
15. Y. D. Cai, D. Clutter, G. Pape, J. Han, M. Welge, and L. Auvil, MAIDS: Mining
Alarming Incidents from Data Streams, (system demonstration), Proc. 2004
ACM-SIGMOD Int. Conf. Management of Data (SIGMOD'04), Paris, France, June 2004.
16. W.-Y. Kim, Y.-K. Lee, and J. Han, CCMine: Efficient Mining of Confidence-Closed Correlated
Patterns, Proc. 2004 Pacific-Asia Conf. on Knowledge Discovery and Data
Mining (PAKDD'04),
17. H.Yu, J. Han, K. C.-C. Chang, PEBL:Web PageClassification
Without Negative Examples, IEEE Transactions onKnowledge
and Data Engineering (Special Issue on Mining and Searching the Web),16(1):
70-81, 2004.
18. G. Dong, J. Han, J. Lam, J. Pei, K. Wang, and W. Zou, MiningConstrained Gradients in Multi-Dimensional Databases,
IEEE Transactions on Knowledge and Data Engineering, 16(6), 2004.
19. X. Yin, J. Han, J. Yang, and P. S. Yu, CrossMine: Efficient Classification across Multiple
Database Relations, Proc. 2004 Int. Conf. on Data Engineering (ICDE'04),
20. J. Wang and J. Han, BIDE: Efficient
Mining of Frequent Closed Sequences, Proc. 2004 Int. Conf. on Data Engineering
(ICDE'04),
21. J. Han, J. Pei, and X. Yan,
"Sequential
Pattern Mining by Pattern-Growth:
Principles and Extensions," in W.
W. Chu and
T. Y. Lin (eds.), Recent
Advances in Data
Mining and Granular Computing (Mathematical Aspects of
Knowledge Discovery), Springer Verlag, 2004.
22. H. Yu, A.
Doan, and J.
Han, "Mining for Information
Discovery on the
Web: Overview and Illustrative Research,"
23. J. Han, J. Pei, and X. Yan,
"Sequential
Pattern Mining by Pattern-Growth:
Principles and Extensions," in W.
W. Chu and
T. Y. Lin (eds.), Recent
Advances in Data
Mining and Granular Computing (Mathematical Aspects of
Knowledge Discovery), Springer Verlag, 2004.
24. P. Bajcsy, J. Han, L. Liu,
J. Yang, "A
Survey of Bio-Data Analysis from Data Mining Perspective," in D. Shasha, et al.
(eds.), Data Mining in Bioinformatics, Springer Verlag,
2004. pp. 9-39.
25. H. Yu, A.
Doan, and J. Han, "Mining for
Information Discovery on the Web:
Overview and Illustrative
Research," N. Zhong and J. Liu (eds.), Intelligent
Technologies for Information Analysis, Springer Verlag,
2004, pp. 131-163.
2003
1. P.
Tzvetkov, X. Yan, and J.
Han, TSP: Mining Top-K
Closed Sequential Patterns, Proc.
2003 Int. Conf. on Data Mining (ICDM'03), Melbourne , FL
2. Y.-K. Lee, W.-Y. Kim, Y. D. Cai, and J.
Han, CoMine: Efficient Mining of Correlated Patterns, Proc. 2003 Int. Conf. on Data Mining (ICDM'03), Melbourne , FL
3. C. Aggarwal, J. Han, J. Wang, and P. S. Yu, A Framework for
Clustering Evolving Data Streams,
Proc. 2003 Int. Conf. on Very
Large Data Bases (VLDB'03),
4.
D. Xin, J. Han, X. Li, and B. W. Wah,
Star-Cubing:
Computing Iceberg Cubes by Top-Down and Bottom-Up Integration, Proc. 2003 Int. Conf. on Very Large Data Bases
(VLDB'03), Berlin , Germany
5.
X. Yan and J. Han, CloseGraph: Mining Closed Frequent Graph Patterns,
Proc. 2003 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining
(KDD'03), Washington , D.C.
6.
H. Yu, J. Yang,
and J. Han, Classifying
Large Data Sets Using SVM with Hierarchical Clusters, Proc. 2003 ACM
SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'03), Washington,
D.C., Aug. 2003.
7.
J. Wang, J. Han,
and J. Pei, CLOSET+:
Searching for the Best Strategies for Mining Frequent Closed Itemsets, Proc. 2003 ACM SIGKDD Int. Conf. on
Knowledge Discovery and Data Mining (KDD'03), Washington , D.C.
8.
H. Wang, W. Fan,
P. S. Yu, and J. Han, Mining
Concept-Drifting Data Streams using Ensemble Classifiers, Proc. 2003 ACM
SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'03), Washington,
D.C., Aug. 2003.
9.
C. Giannella, J. Han, J. Pei, X. Yan
and P.S. Yu, Mining
Frequent Patterns in Data Streams at Multiple Time Granularities, H. Kargupta, A. Joshi, K. Sivakumar,
and Y. Yesha (eds.), Next Generation Data Mining,
2003.
10. X. Yin and J. Han, CPAR:
Classification based on Predictive Association Rules, Proc. 2003 SIAM Int.Conf. on Data Mining (SDM'03),
San Fransisco ,
CA
11. X. Yan, J. Han, and R. Afshar, CloSpan: Mining Closed Sequential Patterns in Large
Datasets, Proc. 2003 SIAM San Fransisco ,
CA
12. K. Wang, Y. He, and J. Han, "Pushing Support
Constraints Into Association Rules Mining", IEEE Transactions on
Knowledge and Data Engineering, Vol. 15, No. 3, May/June 2003.
13. K. Wang, Y. Jiang, J. X. Yu, G. Dong, and J. Han, "Pushing Aggregate
Constraints by Divide-and-Approximate", The
IEEE International Conference on Data Engineering, 2003, Bangalore , India
14. Y. Lu and J. Han, "Cancer
classification using gene expression data," Information Systems
(Special Issue on Data Management in Bioinformatics), 28(4):243-268, 2003.
2002
1.
J. Han, J. Wang,
Y. Lu, and P. Tzvetkov, Mining Top-K
Frequent Closed Patterns without Minimum Support, Proc. 2002 Int.
Conf. on Data Mining (ICDM'02), Maebashi ,
Japan
2.
J. Pei, G. Dong,
W. Zou, and J. Han, On Computing
Condensed Frequent Pattern Bases, Proc. 2002 Int. Conf. on Data Mining
(ICDM'02), Maebashi, Japan, Dec. 2002.
3.
X. Yan and J. Han, gSpan: Graph-Based Substructure Pattern Mining,
Proc. 2002 Int. Conf. on Data Mining (ICDM'02), Maebashi , Japan
4.
H. Yu, K. C. C.
Chang, and J. Han, Heterogeneous
Learner for Web Page Classification, Proc. 2002 Int. Conf. on Data
Mining (ICDM'02), Maebashi ,
Japan
5.
J. Han, and K. C.-C. Chang, Data Mining for Web
Intelligence, Computer, Nov. 2002.
6.
J. Pei, J. Han,
and W. Wang, Mining
Sequential Patterns with Constraints in Large Databases, Proc. 2002
Int. Conf. on Information and Knowledge Management (CIKM'02), Washington , D.C.
7.
Y. Chen, G.
Dong, J. Han, B. W. Wah, and J. Wang, Multi-Dimensional
Regression Analysis of Time-Series Data Streams , Proc. 2002 Int.
Conf. on Very Large Data Bases (VLDB'02), Hong Kong, China, Aug. 2002.
8.
L. V. S. Lakshmanan, J. Pei, and J. Han, " Quotient Cube: How to
Summarize the Semantics of a Data Cube '', Proc. 2002 Int. Conf. on
Very Large Data Bases (VLDB'02), Hong
Kong , China
9.
J. Han, R. B.
Altman, V. Kumar, H. Mannila and D. Pregibon, Emerging Scientific
Applications in Data Mining,
Communications of ACM, 45(8):54-58, 2002.
10. H. Yu, J. Han, and K. C.-C. Chang, " PEBL: Positive Example
Based Learning for Web Page Classification Using SVM '', Proc. 2002
Int. Conf. on Knowledge Discovery in Databases (KDD'02),
11. J. Liu, Y. Pan, K. Wang, and J. Han, " Mining Frequent Item
Sets by Opportunistic Projection '', Proc. 2002 Int. Conf. on Knowledge
Discovery in Databases (KDD'02), Edmonton, Canada, July 2002.
12. J. Han, How Can Data Mining
Help Bio-Data Analysis?, Proc. 2002 Workshop on Data Mining in
Bioinformatics (with SIGKDD02 Conf.)
13. (BIOKDD'02),
14. J. Pei and J. Han, " Constrained Frequent
Pattern Mining: A Pattern-Growth View '', ACM SIGKDD Explorations
(Special Issue on Constrained Data Mining), 2(2), 2002.
15. J. Han, J. Wang, G.
Dong, J. Pei, K. Wang. "
CubeExplorer:
Online Exploration of Data Cubes '',
Proc. 2002 ACM-SIGMOD Int. Conf. on Management of Data (SIGMOD'02),
16. J. Yang, P. Yu, W. Wang, and J. Han, '' Mining Long
Sequential Patterns in a Noisy Environment '', Proc. 2002 ACM-SIGMOD
Int. Conf. on Management of Data (SIGMOD'02), Madison, WI, June 2002.
17. Y. Chen, G. Dong, J. Han, J. Pei, B. W. Wah, and J. Wang, '' Online Analytical
Processing Stream Data: Is It Feasible? '', Proc. 2002 ACM-SIGMOD Int.
Workshop on Research Issues on Data Mining and Knowledge Discovery (DMKD'02),
18. K. Wang, S. Zhou, and J. Han, '' Profit Mining: From
Patterns to Actions '', Proc. 2002 Int. Conf. on Extending Data Base
Technology (EDBT'02),
2001
1.
W. Li, J. Han,
and J. Pei, '' CMAR:
Accurate and Efficient Classification Based on Multiple Class-Association
Rules, '', Proc. 2001 Int. Conf. on Data Mining (ICDM'01),
2.
J. Pei, J. Han,
H. Lu, S. Nishio, S. Tang, and D. Yang, '' H-Mine:
Hyper-Structure Mining of Frequent Patterns in Large Databases '',
Proc. 2001 Int. Conf. on Data Mining (ICDM'01),
3.
H. Pinto, J.
Han, J. Pei, K. Wang, Q. Chen, and U. Dayal, '' Multi-Dimensional
Sequential Pattern Mining'', Proc. 2001 Int. Conf. on Information and
Knowledge Management (CIKM'01), Atlanta, GA, Nov. 2001.
4.
J. Han, M. Kamber, and A. K. H. Tung, '' Spatial Clustering
Methods in Data Mining: A Survey '', in H. Miller and J. Han (eds.),
Geographic Data Mining and Knowledge Discovery,
5.
G. Dong, J.
Han, J. Lam, J. Pei, and K. Wang, '' Mining
Multi-Dimensional Constrained Gradients in Data Cubes '', Proc. 2001
Int. Conf. on Very Large Data Bases (VLDB'01), Rome, Italy, Sept. 2001.
6.
S. H. S. Chee, J. Han, and K. Wang, '' RecTree:
An Efficient Collaborative Filtering Method '', Proc. 2001 Int.
Conf. on Data Warehouse and Knowledge Discovery (DaWaK'01),
7.
W. Jin, K.H.
Tung and J. Han, '' Mining
Top-n Local Outliers in Large Databases '', Proc. 2001 Int. Conf. on
Knowledge Discovery in Databases (KDD'01),
8.
J. Pei, A. K.
H. Tung, and J. Han, '' Fault-Tolerant Frequent
Pattern Mining: Problems and Challenges '', Proc. 2001 ACM-SIGMOD
Int. Workshop on Research Issues on Data Mining and Knowledge Discovery
(DMKD'01), Santa Barbara, CA, May 2001.
9.
J. Han, J. Pei,
G. Dong, and K. Wang, '' Efficient Computation
of Iceberg Cubes with Complex Measures '', Proc. 2001 ACM-SIGMOD
Int. Conf. on Management of Data (SIGMOD'01), Santa Barbara, CA, May 2001.
10. J. Han, H. Jamil, Y. Lu,
L. Chen, Y. Liao, and J. Pei, '' DNA-Miner: A System
Prototype for Mining DNA Sequences '', Proc. 2001 ACM-SIGMOD Int.
Conf. on Management of Data (SIGMOD'01), Santa Barbara, CA, May 2001 (system
demonstration).
11. J. Pei, J. Han, H. Pinto, Q. Chen, U. Dayal, and M.-C. Hsu, '' PrefixSpan:
Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth '',
Proc. 2001 Int. Conf. on Data Engineering (ICDE'01),
12. A. K. H. Tung, J. Hou, and
J. Han, '' Spatial
Clustering in the Presence of Obstacles '', Proc. 2001 Int. Conf. on
Data Engineering (ICDE'01),
13. J. Pei, J. Han, and L. V. S. Lakshmanan,
'' Mining
Frequent Itemsets with Convertible Constraints '',
Proc. 2001 Int. Conf. on Data Engineering (ICDE'01),
14. A. K. H. Tung, J. Han, L. V. S. Lakshmanan,
and R. T. Ng, '' Constraint-Based
Clustering in Large Databases '', Proc. 2001 Int. Conf. on Database
Theory (ICDT'01), London, U.K., Jan. 2001.
2000
1.
J. Han and J.
Pei '' Mining
Frequent Patterns by Pattern-Growth: Methodology and Implications '', ACM
SIGKDD Explorations (Special Issue on Scaleble Data
Mining Algorithms), 2(2), December 2000.
2.
N. Stefanovic, J. Han, and K. Koperski,
'' Object-Based
Selective Materialization for Efficient Implementation of Spatial Data Cubes '',
IEEE Transactions on Knowledge and Data Engineering, 12(6): 938-958, 2000.
3.
H. Lu, L. Feng, and J. Han, '' Beyond
Intra-Transaction Association Analysis: Mining Multi-Dimensional
Inter-Transaction Association Rules '', ACM Transactions on
Information Systems, 18(4): 423-454, 2000.
4.
K. Wang, Y. He
and J. Han, '' Mining
Frequent Itemsets Using Support Constraints '',
Proc. 2000 Int. Conf. on on Very Large Data Bases
(VLDB'00),
5.
E. D. Kim, J.
M. W. Lam, and J. Han, '' AIM: Approximate
Intelligent Matching for Time Series Data '', 2000 Int. Conf. on
Data Wareshouse and Knowledge Discovery (DaWaK'00),
6.
J. Han, J. Pei,
B. Mortazavi-Asl, Q. Chen, U. Dayal,
M.-C. Hsu, '' FreeSpan: Frequent Pattern-Projected Sequential Pattern
Mining'', Proc. 2000 Int. Conf. on Knowledge Discovery and Data
Mining (KDD'00),
7.
J. Pei and J.
Han '' Can We
Push More Constraints into Frequent Pattern Mining? '', Proc. 2000
Int. Conf. on Knowledge Discovery and Data Mining (KDD'00),
8.
J. Pei, J. Han,
and R. Mao, '' CLOSET:
An Efficient Algorithm for Mining Frequent Closed Itemsets
(PDF) '', Proc. 2000 ACM-SIGMOD Int. Workshop on Data Mining and
Knowledge Discovery (DMKD'00),
9.
J. Han, J. Pei,
and Y. Yin, '' Mining
Frequent Patterns without Candidate Generation (PDF)'', (Slides),
Proc. 2000 ACM-SIGMOD Int. Conf. on Management of Data (SIGMOD'00), Dallas,
TX, May 2000.
10. J. Pei, R. Mao, K. Hu, and
H. Zhu, '' Towards
Data Mining Benchmarking: A Test Bed for Performance Study of Frequent Pattern
Mining (PDF)'', Proc. 2000 ACM-SIGMOD Int. Conf. on Management of
Data (SIGMOD'00), (demo paper), Dallas, TX, May 2000.
11. J. Pei, J. Han, B. Mortazavi-Asl,
and H. Zhu '' Mining
Access Patterns Efficiently from Web Logs (PDF)'', Proc. 2000
Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PAKDD'00), Kyoto,
Japan, April 2000.
12. A. K. H. Tung, J. Hou, and
J. Han, '' COE:
Clustering with Obstacles Entities, A Preliminary Study (PDF)'', Proc.
2000 Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PAKDD'00),
13. O. R. Zaοane, J. Han, and H. Zhu, '' Mining Recurrent Items
in Multimedia with Progressive Resolution Refinement (PDF)'', Proc.
2000 Int. Conf. on Data Engineering (ICDE'00), San Diego, CA, March 2000.
Other Papers on KDD
Selected
Publications Since 2000
Selected
Publications Before 2000
MSc. and Ph.D. Theses Related to Data Mining and Database
Systems