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,


Download Dragon Toolkit


Get the Dragon Toolkit source code and binary libraries (including external libraries) and necessary supporting data. Click here to download