Knowledge management is an important weapon for business competition. Many organizations are adopting knowledge management systems. For knowledge management, document management is its key foundation. There is a large amount of procedural knowledge existing in decision documents. This knowledge can illustrate the process and considerations in a decision situation, called episodic. The episodic knowledge can help decision makers understand historical decision process and considerations for future decision making. Therefore, how to discover decision episodes from existing documents is a major research issue in knowledge management.
This research proposes a method for episode mining that integrates automatic document summary techniques, knowledge ontology, and index structures to build the relations and processes of events, and use the Gantt Chart and Flow Chart to portray event processes. We build a prototype system and use a news event as our example to illustrate the feasibility of the proposed approach and demonstrate the results.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0727106-015738 |
| Date | 27 July 2006 |
| Creators | Chuang, Kun-Han |
| Contributors | Jin-shiang Huang, Hsiang-chu Lai, Bing-chiang Jeng, Ting-peng Liang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727106-015738 |
| Rights | campus_withheld, Copyright information available at source archive |
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