Task-stage K-Support:Mining and Supporting Task-relevant Knowledge

• Main Authors: Wei-Hsiao Chen, 陳韋孝
• Other Authors: Duen-Ren Liu
• Format: Others
• Language: en_US
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/47508054351575784582

碩士 === 國立交通大學 === 資訊管理研究所 === 93 === Organizations mainly conduct knowledge-intensive tasks to achieve organizational goals. In such task-based environments, knowledge workers usually accomplish their tasks by stages, while their task-needs may be different at various stages of task performance. Accordingly, an important issue of deploying Knowledge Management Systems is to extract knowledge from the historical task and further support task-relevant knowledge according to workers’ task-needs at different task-stages. This work proposed a task-stage mining method for discovering task-stage needs from historical task executions. The proposed method adopts information retrieval techniques and a modified hierarchical agglomerative clustering (HAC) algorithm to identify task-stage needs by analyzing codified knowledge (documents) accessed or generated during task performance. Task-stage profiles are generated to model workers’ task-stage needs and are used for delivering task-relevant knowledge at various task stages. Finally, we conduct empirical evaluations to demonstrate that the proposed method provides effective knowledge support based on task-stages.