J
Jiawei Han
Researcher at University of Illinois at Urbana–Champaign
Publications - 1302
Citations - 155054
Jiawei Han is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Cluster analysis & Knowledge extraction. The author has an hindex of 168, co-authored 1233 publications receiving 143427 citations. Previous affiliations of Jiawei Han include Georgia Institute of Technology & United States Army Research Laboratory.
Papers
More filters
Journal IssueDOI
Discriminative frequent subgraph mining with optimality guarantees
Marisa Thoma,Hong Cheng,Arthur Gretton,Jiawei Han,Hans-Peter Kriegel,Alexander J. Smola,Le Song,Philip S. Yu,Xifeng Yan,Karsten M. Borgwardt +9 more
TL;DR: This article proposes an approach to feature selection on frequent subgraphs, called CORK, that optimizes a submodular quality criterion, which means that it can yield a near-optimal solution using greedy feature selection.
Proceedings ArticleDOI
Sampling cube: a framework for statistical olap over sampling data
TL;DR: A Sampling Cube framework, which efficiently calculates confidence intervals for any multidimensional query and uses the OLAP structure to group similar segments to increase sampling size when needed is proposed.
Posted Content
Comprehensive Named Entity Recognition on CORD-19 with Distant or Weak Supervision
TL;DR: This CORD-NER dataset with comprehensive named entity recognition (NER) on the COVID-19 Open Research Dataset Challenge (CORD-19) corpus covers 75 fine-grained entity types, which may benefit research on CO VID-19 related virus, spreading mechanisms, and potential vaccines.
Proceedings ArticleDOI
On predicting social unrest using social media
Rostyslav Korolov,Di Lu,Jingjing Wang,Guangyu Zhou,Claire Bonial,Clare R. Voss,Lance M. Kaplan,William A. Wallace,Jiawei Han,Heng Ji +9 more
TL;DR: Results of experimentation with Twitter data collected before and during the 2015 Baltimore events and the information on actual protests taken from news media show a correlation over time between volume of Twitter communications related to mobilization and occurrences of protest at certain geographical locations.
Proceedings ArticleDOI
Collective Multi-type Entity Alignment Between Knowledge Graphs
TL;DR: A novel collective aggregation function tailored for Multi-type entity Alignment, called CG-MuAlign, that relieves the incompleteness of knowledge graphs via both cross-graph and self attentions, and scales up efficiently with mini-batch training paradigm and effective neighborhood sampling strategy.