A Temporal Knowledge Representation Model Using the Knowledge Visualization Technology

• Main Author: 陳育良
• Other Authors: 侯建良
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/56469911446657497677

碩士 === 國立清華大學 === 工業工程與工程管理學系 === 95 === In order to help the knowledge receivers to efficiently and accurately understand the useful knowledge and information from a large number of digital documents, knowledge representation mechanism has become an important issue that the content providers should concern. In the traditional knowledge sharing environment, the abstract temporal knowledge such as temporal information or temporal relations of events is hard to be fully recognized by knowledge receivers in a short time based on the text-oriented knowledge representation scheme. Therefore, a visual representation scheme for the text-based temporal knowledge will support knowledge receivers to efficiently recognize this type of knowledge. The core idea of this research is to extract and tag the temporal terms from text-oriented documents via temporal knowledge analysis procedure. As a result, the temporal relations of events can be derived from the temporal information and the corresponding visualized display of temporal knowledge can also be established according to the temporal information and events. This research develops a methodology for temporal knowledge visualization so that computer systems can automatically convert the text-oriented temporal knowledge into visualized display. A three-phase methodology (including full-text tagging, temporal relations analysis and temporal knowledge visualization) for temporal information extraction, temporal relations analysis and temporal concepts visualization is developed. In addition to the proposed methodology, a Web-based prototype system is developed to evaluate the feasibility of the proposed model and technique. As a whole, this research provides an effective visualization methodology for the knowledge users to improve efficiency for temporal knowledge recognition. The methodology can be further applied in many enterprise activities such as e-training or knowledge management to enhance reuse of temporal knowledge.