【正文】 Ontology I. INTRODUCTION With the further development of work technology and the unceasing emergence of application requirements, semantic web bees a hotspot in research field and a key technology of intelligent work services [1].The semantic web can provide more extensive application functions on the basis of the machine understanding and perform putation at the semantic level. It does not only give clearer and more pletely semantic to the work information and knowledge, but also achieves that puters can understand the work information and knowledge, and the intelligentization of the work data processing and work services. Semantic web bees a more important application in the fields as work services, agentbased distributed puting, semanticbased search engine, semanticbased digital library and so on. At the same time, with the continuous deepening of the applied research, the ontology technique as a key research of semantic web tends to be sophisticated, and there is a formation of semantic metadata describing methods, and development of semantic web begins to enter the practical application stage, such as that there is an initial exploration and application of semanticbased information representation and semanticbased searching in digital libraries and digital museums and other applications[2]. Network educational resource is an important research field on puter education technology and AI. Constructivist learning theory holds that the four elements of the learning environment are context, collaboration, conversation, and meaning built. With the development of puter work and multimedia technology, the ways people learn changed a lot under the influence of the constructivist theory, from traditional teaching to the resourcebased teaching, and then to resourcebased learning [3]. With constructivist learning theory as a guide, it is an important direction of the development of human society in the 21st century digital literacy to build the stablish Network Educational Resources which can select teaching content and teaching pattern according to the actual situation of students, implement individualized instruction for students. Network Educational Resources originated in the development of puteraided education systems, its main feature is that according to the specific circumstances of the user to provide appropriate teaching material, in other words, it has the function of individual teaching, this feature is achieved by means of AI [4]. But, there are some problems of current Network Educational Resources as follows: (1) Low Retrieval efficiency For teaching knowledge is excessive and extensive, the traditional keywordbased search technology can not meet the needs. It is necessary to use appropriate ontology to describe educational resources library and build ontologybased knowledge architecture for solving these problems. (2) Weak semantic High semantic is necessary for munication between different educational application platforms. The reason why making the exchange and sharing of knowledge difficult is that standard of describing the teaching knowledge base is not the same all the time and the knowledge represents in different ways[5]. (3) Lack of intelligence A lot of current teaching systems can not provide Student Information automatically for students to do targeted studying, and make teachers unable to prepare the suitable learning content following the cognitive model of students, and guide the student to learn by their cognitive characteristics and the changes in learning. In response to problems of the current education resources construction and application needs, this paper introduced key technology of semantic to the building of education resources, presented the primary frame of education resources based on semantic web technologies, started with the significant aspects of the building of education resources, such as Semanticbased metadata description, education and resource library ontology model, pattern matching between the resource pool, and discussed the core concept of the framework and key technology. II. ONTOLOGY In this section the most generally accepted understanding of ontology is presented. Since Ontology is a Conceptual Model which is used for describing information systems on the level of semantics and knowledge, it has been used in many fields. Since Ontology is not a static model, it has to have the ability to capture the changes of meanings and relations. In research field of AI, there are many definitions of ontology. Among them, the most frequently adopted is Gruber’, that is,