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Jiawei Han
Michael
Aiken Chair Professor Siebel
School of Computing and Data Science |
Data Mining, Text Mining,
Intelligent Systems
Data Mining Research Group (DMG
Misc Info) |
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Current Research (Selected
Publications)
§ Mining and Leveraging
Knowledge Hypercubes for Complex Applications (NSF-IIS)
§ NSF AI Institute for Molecular Discovery,
Synthetic Strategy, and Manufacturing: Molecule Maker Lab Institute
§ NSF I-Guide: Institute for Geospatial Understanding
through an Integrative Discovery Environment
§ DARPA/INCAS:
“Analytics of Information Influence: Effect Characterization”
Teaching
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UIUC
CS412: An Introduction to Data Warehousing and Data Mining (The course is taught
by Ruby Tahboub, Arindam Benerjee,
Hanghang Tong)
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UIUC
CS512: Data Mining: Principles and Algorithms (The course is taught by
Professor Hanghang Tong)
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UIUC
CS598JH: Text Mining with Large Language Models: 12:30-1:45pm Wednesday/Friday
1035 CIF (Fall 2024)
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Data
Mining Research Group Meeting, Mondays @ Siebel
Center (for DMG group member only)
Books
·
Jiawei Han,
Jian Pei, and Hanghang Tong, Data Mining: Concepts and Techniques, 4thedution,
Morgan
Kaufmann, 2023. (1st ed., 2000)
(2nd ed., 2006) (3rd ed., 2012)
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Jiaming Shen and Jiawei Han, Automated Taxonomy Discovery and Exploration, Springer, 2022 (Series:
Synthesis Lectures on Data Mining and Knowledge Discovery)
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Chao Zhang and Jiawei Han, Multidimensional Mining of Massive Text Data, Morgan &
Claypool Publishers, 2019 (Series: Synthesis Lectures on Data Mining and
Knowledge Discovery)
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Xiang Ren and Jiawei Han, Mining
Structures of Factual Knowledge from Text: An Effort-Light Approach, Morgan &
Claypool Publishers, 2018 (Series: Synthesis Lectures on Data Mining and
Knowledge Discovery)
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Jialu Liu, Jingbo Shang and
Jiawei Han, Phrase Mining
from Massive Text and Its Applications, Morgan &
Claypool Publishers, 2017 (Series: Synthesis Lectures on Data Mining and
Knowledge Discovery)
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Chi Wang and
Jiawei Han, Mining Latent Entity Structures, Morgan &
Claypool Publishers, 2015 (Series: Synthesis Lectures on Data Mining and
Knowledge Discovery)
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Yizhou Sun and
Jiawei Han, Mining Heterogeneous Information
Networks: Principles and Methodologies, Morgan & Claypool
Publishers, 2012 (Series: Synthesis Lectures on Data Mining and Knowledge
Discovery)
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Manish Gupta, Jing
Gao, Charu Aggawal, and Jiawei Han, Outlier
Detection for Temporal Data, Morgan & Claypool Publishers, 2014
(Series: Synthesis Lectures on Data Mining and Knowledge Discovery)
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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 ed.), Taylor & Francis, 2009.
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Philip S. Yu, Jiawei Han, and Christos
Faloutsos (eds), Link
Mining: Models, Algorithms, and Applications, Springer, 2010.
·
Ashok N. Srivastava and Jiawei Han,
Machine
Learning and Knowledge Discovery for Engineering Systems Health Management (Chapman & Hall/CRC Data Mining and Knowledge Discovery
Series), Taylor & Francis, 2011
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David Lo,
Siau-Cheng Khoo, Jiawei Han, and Chao Liu (eds.), Mining Software Specifications: Methodologies and
Applications (Chapman & Hall/CRC Data Mining and
Knowledge Discovery Series), Taylor & Francis, 2011
Completed Research Projects
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OLAPing
and Multi-Dimensional Search and Analysis of Text Data (Event Cube: NASA)
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Pattern Discovery:
Classification, Clustering and Outlier Analysis
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Towards On-Line Analytical
Mining of Heterogeneous Information Networks
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Endowing Biological
Databases with Analytical Power: Indexing, Querying, and Mining of Complex
Biological Structures
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Mining Dynamics of Data
Streams in Multi-Dimensional Space
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Knowledge
Discovery in Cyberphysical Systems
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MoveMine:
Mining Knowledge from Massive Moving Object Data
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Conflicts to Harmony:
Truth Discovery (NSF/IIS)
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Information
Network Academic Research Center: Network
Science-Collaborative Technology Alliance
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NIH BD2K: KnowEng (Knowledge Engine
for Genomics) Center: Construction and Mining of Biological Networks
· Multi-Dimensional Structuring, Summarizing and Mining of Social Media Data (NSF/IIS)
· StructNet: Constructing and Mining Structure-Rich Information Networks for Scientific Research (NSF/IIS)
· Taming Big Networks via Embedding (NSF/IIS-BIGDATA)
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DARPA/KAIROS:
“RESIN: Reasoning about Event Schemas for Induction of kNowledge”
Publications
(@DBLP) Google
Scholar Citations
Back to Data
and Information Systems Laboratory, Siebel
School of Computing and Data Science, Univ.
of Illinois at Urbana-Champaign