14th Annual International Florida Artificial Intelligence Research Symposium Special Track on Knowledge Management Description: Knowledge Management (KM) is an increasingly important new business movement that promotes the creation, sharing and leveraging of knowledge within an organization to maximize business results. Supporters of the Knowledge Management movement say "effective knowledge management pays off in fewer mistakes, less redundancy, quicker problem solving, better decision making, reduced research development costs, increased worker independence, enhanced customer relations, and improved services." Since Knowledge Management tools provide access to explicit company knowledge, it is easy to learn from previous experiences. "Learning" companies "benefit by not repeating costly mistakes, and by reducing time-to-market in Research & Development projects. The context of Knowledge Management (KM) is to capture and re-use the investments in research and development as a vital part of a project. Eliciting and harvesting knowledge changes a normal organization into a "learning" organization capable of quickly and efficiently finding solutions to new problems, as well as, reusing and adapting previous solutions. The real question now becomes, how can a company better elicit and reuse its knowledge? There are various tools and practices to increase the organization's learning ability. It is up to the organization to adopt the right methodologies and software tools that best address their demands for storage and reusability of past project experiences. Knowledge repositories are created with the sole purpose of storing explicit knowledge of organizational information. This includes storing explicit decisions as well as the reasons why decisions were made. Access to explicit knowledge should be intuitive and organized. Intranet and GroupWare tools are implemented to gather knowledge as teams create it in project collaborations, and to help them work together in an organized and coordinated fashion. There are many different types of tools aiming to provide solutions to different challenges of the Knowledge Management context environment. It is equally important to identify how an organization improves the knowledge sharing culture among their employees. This track focuses on the effective design and development of state-of-the-art KM applications. This track includes research in related topics including cultural implications in creating a "knowledge sharing" environment versus one of "knowledge-is-power". Topics of interest include all aspects of relevant to KM, including related AI applications based on traditional AI methods such as Case-Based-Reasoning, neural networks, knowledge representation, reasoning, knowledge engineering, cognitive issues, validation of knowledge repositories, etc. People concerned with the design, development and use of KM and interested in presenting a position paper (or report on results, demonstrate a working system) that discusses their contribution to the topics mentioned above are invited to submit a paper. The goal of this track is to continue a long-term effort in: - integrating works that address important issues and current unsolved problems with regard to research in KM; - publicizing the contribution of AI in KM by maintaining contacts and advertising sharable resources (mailing list, archives, Web site, etc.); - determining what is common in all Knowledge Management domains so that the KM community can further this work; Authors are invited to submit: A position statement, extended abstract, reports, results, or any other paper addressing topics such as those listed above. Submission requirements: Length: 1200 to 1600 words The review is blind. Author names and affiliations are to appear ONLY on a separate cover page. Please indicate on that cover page the primary author, the presenter (if different) and all appropriate contact information (email, phone, fax, etc.). Medium: a. Electronic submission: Email your submission to becferi@fiu.edu ASCII text is most reliable Every effort will be made to accommodate MS Word, Postscript and other formats. b. Hard copy submission: 12 pt font, 10 double spaced pages, 1" borders Send 4 copies of the paper to: Dr. Irma Becerra-Fernandez Florida International University Decision Sciences and Information Systems, BA 250 Miami, FL 33199 Important Dates: Paper submission deadline: November 27th, 2000 Notification of Acceptance-Rejection: January 11, 2001 Camera Ready Copy: March 3, 2001 (strict deadline!) Conference: May 21th - 23th , 2001 Track Program Committee Chair: Dr. Irma Becerra-Fernandez Florida International University Decision Sciences and Information Systems, BA 256A Miami, Fl becferi@fiu.edu (305)348-3476 Members: Dr. David Aha Navy Center for Applied Research in Artificial Intelligence Naval Research Lab Washington, D.C. Dr. Dinesh Batra Florida International University Decision Sciences and Information Systems Miami, FL Dr. Alberto J. Canas Institute for Human and Machine Cognition University of West Florida Pensacola, FL Dr. Michael Freeman NASA-Ames Research Laboratory Moffet Field, California Dr. Rajiv Sabherwal Information and Management Services Florida State University Tallahassee, Florida Dr. Rosina Weber Computer Science, University of Wyoming Navy Center for Applied Research in Artificial Intelligence Washington, D.C.