標題: | Mining and supporting task-stage knowledge: A hierarchical clustering technique |
作者: | Liu, Duen-Ren Wu, I-Chin Chen, Wei-Hsiao 資訊管理與財務金融系 註:原資管所+財金所 Department of Information Management and Finance |
關鍵字: | knowledge-intensive task;task-relevant knowledge;task-stage mining;hierarchical agglomerative clustering |
公開日期: | 2006 |
摘要: | In task-based business environments, organizations usually conduct knowledge-intensive tasks to achieve organizational goals; thus, knowledge management systems (KMSs) need to provide relevant information to fulfill the information needs of knowledge workers. Since knowledge workers usually accomplish a task in stages, their task-needs may be different at various stages of the task's execution. Thus, an important issue is how to extract knowledge from historical tasks and further support task-relevant knowledge according to the workers' task-needs at different task-stages. This work proposes a task-stage mining technique for discovering task-stage needs from historical (previously executed) tasks. The proposed method uses information retrieval techniques and a modified hierarchical agglomerative clustering algorithm to identify task-stage needs by analyzing codified knowledge (documents) accessed or generated during the task's performance. Task-stage profiles are generated to model workers' task-stage needs and used to deliver task-relevant knowledge at various task-stages. Finally, we conduct empirical evaluations to demonstrate that the proposed method provides a basis for effective knowledge support. |
URI: | http://hdl.handle.net/11536/17148 |
ISBN: | 978-3-540-49998-5 |
ISSN: | 0302-9743 |
期刊: | Practical Aspects of Knowledge Management, Proceedings |
Volume: | 4333 |
起始頁: | 178 |
結束頁: | 188 |
顯示於類別: | 會議論文 |