The Artificial Intelligence Laboratory conducts sophisticated information systems research and has attained significiant contributions in machine learning, visualization, knowledge management, and many other areas of endeavor. Our latest research projects include:
A major goal for healthcare-related IT is to develop trusted healthcare systems that offer relevant decision support to clinicians and patients, and in particular, provide “just in time, just for me” advice at the point of care.
E-commerce applications present unique challenges and opportunities for developing various data mining, text mining, and web mining techniques for business intelligence and knowledge management purposes.
The development of advanced information technologies, systems, algorithms, and databases for national security-related applications, through an integrated technological, organizational, and policy-based approach.
The AI Lab Dark Web project is a long-term scientific research program that aims to study and understand the international terrorism (Jihadist) phenomena via a computational, data-centric approach.
Sports data mining includes data mining, web mining, web mashups, and cloud computing in various sports related applications. Dr. Chen published the first Sports Data Mining book in 2010.
Cross-jurisdictional information sharing, analysis, visualization and research for the law enforcement and intelligence community for border and national security.
Use of the BioPortal system will improve the ability of public health practitioners to detect, and maintain situational awareness of outbreaks of emerging diseases and bioterrorist attacks.
Nanotechnology holds the promise of revolutionizing a wide range of application areas and has been recognized by most countries as critical to a nation's future technology competence.
To develop text mining and data mining techniques to support automated extraction and inference of regulatory pathways from biomedical literature and experimental data.
Much of our earlier work is still accessible via the Web. Some of our previously funded projects have included the following:
Developed text mining and data mining techniques to support automated extraction and inference of regulatory pathways from biomedical literature and experimental data.
Developed techniques to enhance information retrieval and knowledge management of large digital collections.
A graphical interface that summarized the discussion content and participants behavior from an archive of a computer mediated communication (CMC) process.
To study the research issues involved, we designed and implemented a toolkit, called SpidersRUs, for multilingual search engine creation.
The project integrated system and human-generated classification systems and created a high-performance digital library classification system (i.e., the OOHAY system).
Examined and experimented with knowledge management techniques for groupware and CSCW systems.
Developed techniques to support cross-Language Information Retrieval (CLIR) and cross-lingual semantic interoperability.