Meta-level patterns for interactive knowledge capture

Current knowledge acquisition tools have limited understanding of how users enter knowledge and how acquired knowledge is used, and provide limited assistance in organizing various knowledge authoring tasks. Users have to make up for these shortcomings by keeping track of past mistakes, current status, potential new problems, and possible courses of actions by themselves. In this paper, we present a novel extension to existing knowledge acquisition tools where the system organizes the episodes of past interactions through a set of declarative meta-level patterns and improves its suggestions based on relevant episodes. In particular, we focus on 1) assessing the level of confidence in suggesting an action, 2) suggesting how a knowledge authoring action can be done based on successful past actions, and 3) monitoring dynamic changes in the environment to suggest relevant modifications in the knowledge base. A preliminary study with varying synthetic user interactions shows that this meta...

• Type: Conference
• Year: 2005
• Where: KCAP
• Authors: Jihie Kim
• Keywords: KCAP 2005, Knowledge Acquisition Tools, Knowledge Authoring Tasks, Users Enter Knowledge