In recent years, along with the rapid developments of information technology and the continuous improvements of the network learning platforms, more and more people prefer to choose online learning. As the growing requirement of people’s demand for resources, the resources in the network become extremely expand. It seems to be a big challenge to the learners to find suitable learning resources. It has been the focus of experts and scholars concern which is how to find a better way to help learners get resources from the vast network appropriately. Except that, the experts still pay attention to improve the utilization of the Internet resources and learners’ learning efficiency. With the emergence of social tagging which is used to found in the social sites network in Web 2.0, it has brought a new train of thought to solve the problem of recommending network resources. Social tagging combines the users and resources together, and builds a recommendation mechanism based on that gradually. Besides, it is a bold attempt to move the mechanism into learning areas.The thesis discusses overseas and domestic research status about the social tagging based on the personalized recommendation. Besides, the thesis uses the social network analyses and content analyses to discover the mechanism of the typical foreign web sites which used social tagging based recommendation. In addition, the advantages and disadvantages of the mechanism are generalized. Besides, based on all of them, the thesis provides the construction of moving the mechanism to the area of learning. Furthermore, the questionnaires method is feasible to analysis the requirement of learners. Combines with the results of the analysis and functional design idea, the thesis puts forward the model of learning resources personalized recommendation based on social tagging. The model is put into the prototype with the support of the related technologies. It is helpful to summarize the feedback of the learners who operated it through the way of interviewing method. The thesis discusses the social tagging based recommendation in two respects which are theory and practice. In this way, the thesis provides the certain experiences for the further development of the related research about the personalized recommendation of learning resources based on social tagging. |