Information Analysis & Management
Research Projects
Publications
Patents
Staff
Information Analysis & Management
We envision a user intent-aware services environment
(consisting of communications networks, distributed processing resources,
and databases) that senses the real intent of its users and renders services
to their satisfaction. It actively learns from past experience, draws
on distributed information and resources, and utilizes advanced algorithms
to determine its plans and actions.
This vision represents a paradigm shift by transforming a whole network
(enterprise, public and combination thereof) into an intelligent system
into which a user sends a request/query, and through some interactions
(allowing for the system to extract what the user wants), the system
takes actions that best meet the user's expectations. The system can
recognize the value of the information in the network from different
perspectives and criteria. This feature frees users from the burden of
information management and gives them flexibility and adaptability in
planning, decision-making, and actions, causing overall process improvement.
This paradigm shift will not happen overnight, perhaps taking a decade
or even more. However, breakthroughs in key enabling technology areas
will bring about evolutionary steps, each of which leads to near term
business opportunities. A collection of such steps will eventually cause
the revolutionary change.
In any system design, it is imperative to make sure that the system performs
above certain requirement thresholds (e.g., speed, accuracy, and cost)
imposed by an application; otherwise it won't be used. We focus research
on areas where breakthroughs will render an important technology useful
by surpassing a particular threshold.
The technical challenge in realizing a user intent-aware services environment
is to understand users' intent correctly and quickly enough.
If a user's intent is to get information needed in a decision making
process, a major technical challenge is to extract real intent from keywords,
context and a user profile database, then filter, extract, and combine
information from multiple sources; we refer to that as intelligent information
integration. Our research in this area already uses Support Vector Machine
(SVM) technology to improve classification, returning higher relevance
information to a query. Enhancing data mining technology to a much higher
intelligence level is necessary for crossing the correctness/efficiency
threshold required by serious business applications.
We are conducting research on middleware software framework, advanced
information retrieval and machine learning applications among others.
Internet-based information services are getting mature and diverse, so
it is much more important to provide on-demand, trustworthy knowledge
distribution and sharing over a cost-efficient, scalable infrastructure.
We will focus on the intelligent information integration paradigm to
contribute to process reengineering for Internet-initiated solution and
service business.
Our approach to research is unique. We are exploring new innovative technologies,
working with advanced users, entrepreneurs-in-residence, and strategic
partners to identify real enterprise/market/user pains and to get early,
continuous feedback on potential solutions.
Research Projects
Publications
Patents
Staff
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