A framework of ontological semantic knowledge tree for vertical search engine

Search engine is becoming more and more important in our life. Traditional search technologies, however, cannot provide the required information for the users. Future search engine must be intelligent and semantic. We develop a vertical search engine based on ontological semantic knowledge tree model. In this model, concept is regarded as the basic knowledge representation unit. And attribute, relation and behavior describe concept. On the basis of characteristics of Chinese, concept is divided into primitive concept, semantic binding concept, semantic state concept and semantic logical concept. Then these concepts are organized by tree hierarchical structure to describe a specific domain. And this model has been proved successfully to many domains such knowledge reasoning of agriculture and knowledge service of automobile etc. Subsequently, the architecture of search engine are described, especially, semantic classification has been proved practical. Finally, because this tree is expansible, vertical search engine can be built on any domain.