A Semantic Retrieval and Alert Notification of Enterprises Climate Adaptation Information System

• Main Authors: Jyun-Siang Lai, 賴俊翔
• Other Authors: Jyi-Ta Chen
• Format: Others
• Language: zh-TW
• Published: 104
• Online Access: http://ndltd.ncl.edu.tw/handle/24768447624945517107

碩士 === 南臺科技大學 === 資訊管理系 === 103 === At present, information science and technology are booming, volume of data from Internet have emerged very huge. With the evolution time, we face the problem is data processing became more complex. Currently, the information retrieval technology is still relying on a general keyword search technology mostly. In the area of climate and disasters, querying from network will acquire a lot of different information, it makes the general users get excessive data but not needing. Many climate information systems are lack of warning design for enterprises. For the purpose of providing weather information easily and quickly for users, and to solve problems of business losses about climate disaster. We develop a corporate climate adaptation information system with the function of semantic retrieval and warning notification. The system uses a network crawler to capture real-time weather information from major climate information websites, and collecting the open data providing by the government. We design a friendly information presentation platform that allows users to find information what they want quickly. The semantic query function of system with climate disasters ontology repository and semantic inference engine analyzes related queries sentences those enter by users. All sentences are typed in vocabulary quiz-form and query about weather, disasters, climate adaptation etc. knowledge. By continuous Q&A operation between users and UI response, enhancing the accurate of access on climate information. The interpretation techniques is the use of climate warning rules to reason climate information immediately. If climate situation reaches the alert notification conditions, warning notices will be sent to the enterprise immediately, and reaching the effectiveness of early disaster and reducing business losses about climate disaster.