Accident prevention system based on semantic network
Yang Jian-xiong, Junzo Watada · 2008
As humans handle huge and dynamic information in their daily life, such information is structurally complex and ever growing. Nowadays, the most typical information should be the World Wide Web. It is a fertile knowledge sea which humans encounter in their life individually as well as in business. Therefore, Web mining is one of most important techniques. A new generation of web mining techniques is developed to analyze Web information by means of searching, recommending, surfing and visualizing the Web. A semantic network is one of new ways for web content mining which takes advantage for both of a fuzzy logical search and semantic analysis. The objective of this paper is to build an accident prevention system by means of the semantic network. The system is built from a number of ranking algorithms based on generality and novelty measures extracted from an accident database.