Selected Publications Since 2000
Selected Publications Since
2000
Selected Publications Before
2000
MSc. and Ph.D. Theses Related to Data Mining and Database
Systems
2008
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
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.
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.
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.
Deng Cai,
Xiaofei He, and Jiawei Han,
“Sparse
Projections over Graph”, Proc. 2008 AAAI Conf. on Artificial
Intelligence (AAAI-08), Chicago, Illinois, July 2008.
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.
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.
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.
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.
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.
Sangkyum Kim, Xin Jin and Jiawei Han, “SpaRClus:
Spatial Relationship Pattern-Based Hierarchical Clustering”, Proc. 2008
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.
Deng Cai,
Xiaofei He, and Jiawei Han,
"Training
Linear Discriminant Analysis in Linear Time",
Proc. 2008 Int. Conf. on Data Engineering (ICDE'08),
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.
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),
Dong Xin and Jiawei Han, "P-Cube: Answering
Preference Queries in Multi-Dimensional Space", Proc. 2008 Int. Conf.
on Data Engineering (ICDE'08),
Jiawei Han, Xiaoxin Yin and Philip S. Yu, "Exploring the Power of Links
in Scalable Data Analysis", ICDE'08 conference tutorial, Cancun,
Mexico, April 2008 (available after the conference).
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.
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.
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.
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), Rio de Janeiro,
Brazil, Oct. 2007.
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
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.
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.
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
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.
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).
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, Sept. 2007.
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
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.
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
Deng Cai, Xiaofei He and Jiawei Han, “Isometric Projection”, in Proc. 2007 AAAI Conf. on Artificial Intelligence
(AAAI-07), Vancouver, B. C., Canada, July 2007.
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
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
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.
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.
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)
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.
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
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.
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)
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),
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),
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.
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
Hongyan
Liu, Ying Lu,
Kaushik
Chakrabarti, Venkatesh Ganti,
Wen Jin,
Anthony K. H. Tung,
Hongyan
Liu,
Charu
Aggarwal,
Hongyan
Liu,
2005
Wen Jin,
Martin Ester and
H. Liu,
X. Yin, J. Han, “An Efficient
Multi-relational Naïve Bayesian Classifier Based on Semantic Relationship Graphs”,
in Proc. 2005 ACM-SIGKDD Workshop on Multi-Relational Data Mining
(KDD/MRDM'05),
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.
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.
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.
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),
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),
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),
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),
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),
S. Cong,
J. Han, and D.
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.
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),
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.
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.
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.
H.
Cheng, X. Yan, and J. Han, “SeqIndex:
Indexing Sequences by Sequential Pattern Analysis”, in Proc. 2005
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),
X. Yan,
X. J. Zhou, J. Han, “Mining Closed
Relational Graphs with Connectivity Constraints”, in Proc. 2005 Int.
Conf. on Data Engineering (ICDE'05),
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),
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.
2004
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 (PKDD’04),
Pisa, Italy, Sept. 2004.
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),
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),
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),
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),
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),
Y. Li, J. Han, and J. Yang, “Clustering Moving
Objects”, Proc. 2004 Int. Conf. on Knowledge Discovery and Data
Mining (KDD'04),
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),
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.
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.
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),
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),
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.
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.
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.
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),
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.
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.
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),
J. Wang
and J. Han, “BIDE: Efficient Mining of Frequent Closed
Sequences”, Proc. 2004 Int. Conf. on Data Engineering
(ICDE'04),
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.
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.
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.
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.
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
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
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
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),