Proactive search enabled context-sensitive knowledge supply situated in computer-aided engineering

Processing complex and non-routine tasks, engineers face frequent knowledge shortage. While an expert system requires much effort to develop and a general search engine is blamed for passiveness in meeting people’s knowledge demand, we propose in this paper a context-sensitive knowledge supply method which aims at meeting users’ unuttered knowledge need bred in computer-aided engineering (CAE) tasks. To this end, concepts involved in a task are extracted and used for perceiving various problematic situations which may occur; and keyword-based search and text parsing techniques are combined to retrieve possible remedies from unstructured knowledge carriers. The proposed method is tested in situation of finite element analysis (FEA), a typical CAE task, where novice engineers receive sentential knowledge recommendations extracted from webpage. Experiment results show that context-sensitive knowledge supply can increase an engineer’s knowledge about the current task and make the individual more prepared for future challenges.