Artificial Intelligence & Knowledge Management
Papers from the AAAI Workshop
Bradley Whitehall, Chair
As competitive pressures increase, many organizations realize that to prosper in the future they must manage their most valuable asset, knowledge, more carefully. Knowledge management is concerned with issues involved with identifying, collecting, storing, evaluating, indexing, structuring, extracting, and presenting knowledge used to improve an organization's productivity. Knowledge management systems should unobtrusively collect knowledge as work is being completed and present knowledge in a just-in-time fashion for effective problem solving. Knowledge management systems need to be flexible and adaptive. Research in many areas will impact knowledge management.
This workshop will focus on the "problem in the large." That is, how do knowledge acquisition, knowledge representation, knowledge discovery, agents, adaptive systems, and other techniques function in a diverse, often ill-structured environment and what, if any, organizational constraints must exist to be able to successfully manage knowledge. Issues involved with adding context and other meta-data along with using ontologies to promote the sharing of relevant information are important topics for this workshop.
The goal of this workshop was to bring AI researchers and researchers from communities associated with knowledge management together to share experiences, solutions, and approaches to outstanding problems. The problems are large, but some work has been successful in solving portions of the problem.