About Us

We concentrate on the research and development of concepts, methodologies, and software systems for the acquisition, modeling, representation, and management of knowledge critical to situational awareness and decision making. Our research specially focuses on applying the Knowledge Engineering (KE) techniques to Web Intelligence (WI) tasks for efficient information retrieval, analysis, mining, and effective utilization.

"Knowledge Engineering (KE) refers to the building, maintaining and development of knowledge-based systems. It has a great deal in common with software engineering, and is related to many computer science domains such as artificial intelligence, databases, data mining, expert systems, decision support systems and geographic information systems. Knowledge engineering is also related to mathematical logic, as well as strongly involved in cognitive science and socio-cognitive engineering where the knowledge is produced by socio-cognitive aggregates (mainly humans) and is structured according to our understanding of how human reasoning and logic works." [http://en.wikipedia.org/wiki/Knowledge_engineering]

"Web Intelligence (WI) has been recognized as a new direction for scientific research and development to explore the fundamental roles as well as practical impacts of Artificial Intelligence (AI) (e.g., knowledge representation, planning, knowledge discovery and data mining, intelligent agents, and social network intelligence) and advanced Information Technology (IT) (e.g., wireless networks, ubiquitous devices, social networks, wisdom Web, and data/knowledge grids) on the next generation of Web-empowered products, systems, services, and activities. It is one of the most important as well as promising IT research fields in the era of Web and agent intelligence." [http://wi-consortium.org/] WI is regarded as the key research field for the development of the Wisdom Web (including the Semantic Web).

We believe that there are different types of knowledge, and there are different ways of representing and using knowledge. Right approach and technique should be developed and used to aid the acquisition, analysis, validation and re-use of the knowledge. The KEWI research is based on the principles that:

  1. It is difficult for humans to express what information he/she is looking for accurately and precisely because (a) the human mind often works in a vague and imprecise mode, and (b) the means humans are using to express their mind are not accurate and precise (e.g., natural language expressions are often ambiguous)
  2. The information objects are complex ensembles, containing multi-folds of semiotic aspects and multi-folds of semantic interpretations.

Our research projects span from (1) Probabilistic (Bayesian) Reasoning in Fact-Proposition Space for more precise knowledge representation and discovery to (2) Incremental Ontology Building for more effective modeling (and matching) of human mind (and intention) and information objects, (3) Smart Searching Capability for more powerful Web query features, (4) Semeotic Pattern Classification for more accurate information tagging, annotation, and filtering, and ultimately (5) Tailored Information Delivery and Service (TIDS) for providing timely and critical Decision Support under the condistions of situational uncertainties. We address the problems encountered in the processes for acquisition of explicit, formalizable knowledge from open Web sources that contain relevant information in implicit or not directly accessible form. The projects involve with the development and application of AI techniques in machine learning and data mining for more efficient information retrieval, and knowledge extraction.

The theme of our projects thus is WYGIWYN™—What You Get Is What You Need—which aims to provide Web users with on-time, on-purpose, and on-target information services. Knowledge objects dealt with in these projects include concepts, logics, attributes, values, meta-data, ontology, processes and relationships, as represented by nodes and links on a ladder or diagram. We strive to develop unique, efficient Web 2.0 tools for querying and analyzing the knowledge objects more efficiently, significantly reducing the information overloading, and assisting Web users in more effective use of Web information.

Link to WIC: The Web Intelligence Consortium (WIC) (http://wi-consortium.org/) is an international, non-profit organization dedicated to advancing world-wide scientific research and industrial development in the field of Web Intelligence (WI). It promotes collaborations among world-wide WI research centers and organizational members, technology showcases at WI related conferences and workshops, WIC official book and journal publications, WIC newsletters, and WIC official releases of new industrial solutions and standards.