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

被引:9
|
作者
Song, Bo [1 ]
Jiang, Zuhua [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai 200240, Peoples R China
基金
高等学校博士学科点专项科研基金;
关键词
Knowledge reuse; Context-sensitive; Problematic situation; Proactive search; Computer-aided engineering; INFORMATION-RETRIEVAL; EXPERT-SYSTEM; DESIGN; REUSE; FRAMEWORK; HYBRID;
D O I
10.1016/j.aei.2012.10.006
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:66 / 75
页数:10
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