Funded Projects
·
PI: NSF A Novel
Paradigm for Detecting Complex Anomalous Patterns in Multi-modal,
Heterogeneous, and High-dimensional Multi-source Data Sets (NSF IIS 1815256, $249.7K,
09/01/2018-08/31/2021)
·
EAGER: A
Novel Set of Computational Methods for Mining Nonlinear and High-order
Relationships, (NSF IIS 1744661, $150K, 08/01/2017-07/31/2019)
·
PI: I/U CRC Phase II: Center for Visual
and Decision Informatics (CVDI) (NSF IIP 1150431, $200K (NSF), 03/15/2017-02/31/2020)
·
PI: I/U CRC Phase I: Center for Visual and
Decision Informatics (CVDI) (NSF IIP 1160960, $300K (NSF), $1.2M (industry
members) 02/15/2012-01/31/2017)
·
PI:NSF I/UCRC
CORBI: CVDI: Modeling,
Visualization, and Understanding of Large Data Sets (NSF IIP 1433098, $49,999(NSF), $50K (IAB),
02/15/2014-01/31/2016)
·
PI:NSF Large-Scale Predictive Modeling and Visualization
based Gap Analysis (NSF IIP 1332024, $99K, 07/01/2013-06/30/2015)
·
PI: Integrating
and Mining Bio-Data
from Multi Sources in Biological Networks (NSF CCF 0905291, $353K,
10/01/2009-09/30/2013)
·
PI:EAGER:Graph-based Theoretical Models and Mining
Algorithms for Bioinformatics Data Analysis (NSF CCF 1049864, $150K,
09/01/2010-08/31/2012)
·
PI: Planning
Grant: Industry & University
Cooperative Research Center for Visual Decision Informatics (NSF IIP
0934197, $10K, 09/01/2009-08/31/2010)
·
Co-PI: BIBM Conference: Fostering
Interdisciplinary Research and Education in Bioinformatics and Biomedicine (NSF
IIS 0906601, $20K, 10/01/2009-09/30/2010)
·
PI: Career: A Unified Architecture for Data
Mining Large Biomedical Literature Databases (NSF IIS 0448023, $415K, 03/15/2005-02/28/2010)
·
PI: High
Performance Rough Sets Data Analysis in Data Mining (NSF CCF 0514679, $102K,
07/15/2005-07/31/2008)
·
PI: Getting Value from Data: Center for
Visual and Decision Informatics, (USA Institute of Museum and Library Services, LG-00-11-0355-11,
$60K, 12/01/2011-11/30/2013)
·
Co-PI: Tobacco Policy and Control Initiative – Communities Putting Prevention to Work (CPPW)
(CDC, $57K, 10/1/2011-03/18/2012)
·
Co-PI:Travel Award
for the 2011 IEEE International Conference on Bioinformatics and Biomedicine
(NSF CCF 1142717, $16K, 08/01/2011-07/31/2012)
·
Co-PI: Evaluation
of Cancer Prevention and Control and other Chronic Disease Programs (CDC/PA
Dept. of Health, $1.55M, 07/01/2011-06/30/2016)
·
Co-PI: Co-PI:
Penn State Cancer Education Network Evaluation Phase 2 (PA Dept. of Health/CDC,
$399.3K, 07/01/2008-06/31/2010)
·
CO-PI: Evaluation
of Pennsylvania Comprehensive Cancer Control Program (PA Dept. of Health/CDC,
$151K, 07/2007-06/2008)
·
Co-PI: Penn
State Cancer Education Network Evaluation Phase 1 (PA Dept. of Health,
$500K, 04/01/2006-07/31/2008)
·
Co-PI: The
Drexel University GAANN Fellowship Program: Educating Renaissance Engineers
(US Dept. of Education, around $700K ($504K from DoE + Drexel Matchup),
9/1/2006-7/31/2009)
·
Co-PI: Center for Public Health Readiness
and Communication (PA Dept. of Health, $1.5M, 09/01/2004-08/31/2007)
·
Co-PI: Origin and
evolution of genomic instability in breast cancer (PA Dept. of Health Tobacco
Formula Grant, $100K, 05/01/2004-04/30/2005)
·
Co-PI: Systems
biology approach to understand protein-protein interactions (PA Dept. of Health
Tobacco Formula Grant, $50K, 05/01/2004-04/30-2005)
The Dragon ToolKit
The Dragon Tooolkit is a cute
Java-based development package for academic research use in language modeling
(LM) and information retrieval (IR). Language modeling has recently emerged as an
attractive new framework for text information retrieval and text mining (TM).
However, most Java-based free search engines such as Lucene does not support LM
very well. The Lemur toolkit is designed for LM and IR, but written in C and
C++, which may be a hindrance to people who prefer Java programming. Basically,
the dragon toolkit is tailored for researchers who work on large-scale LM and
IR and prefer Java programming. Moreover, different from Lucene and Lemur, it
provides built-in supports for semantic-based IR and TM. The dragon tookit seamlessly intergrates and
implements a set of NLP tools, which enable the toolkit to index text
collections with various representation schemes including words, phrases,
ontology-based concepts and relationships. However, to minimize the learning
time, we intentionally keep the package small and simple. The toolkit does not
have some features including distributed IR and cross-language IR which are
part of Lemur toolkit.
How to Cite Dragon Toolkit
If
you are using the Dragon Toolkit for research work, please cite it in your
published papers:
Zhou, X.,
Zhang, X., and Hu, X., The Dragon Toolkit, Data Mining & Bioinformatics
Lab, The College of Computing and Informatics at Drexel University, http://dragon.ischool.drexel.edu/
Download Dragon Toolkit
Get the
Dragon Toolkit source code and binary libraries (including external libraries)
and necessary supporting data. Click here to download