The Design And Implementation Of Recommendation System Based On Double Clustering

With the soaring development in computer network technologies and the continuously enhancing attentions paid by most country authorities toeducation, the phenomenon that the people make use of the network as a modern communication method to carry on educating becomes quite widespread. Nowadays, not only are the categories of the network educational resources various, but also the number of them is very huge as well. Therefore, it needs to develop the network educational resource management software to effectively manage the network educational resources, efficiently withdraw and organize the resource information that the user needs from a great deal of the network educational resources at any time.The aim of the Educational Resource Network is to organize and manage various kinds of network educational resources effectively so that people can share and access them efficiently, and to increase the speed of network educational resources developing and utilizing, and just to further promote the development of educational network. As an important computer application on e-commerce, recommendation system not only wins extensive concern in the research domain, but also gets widely applied to the e-commerce systems. However, the recommender system still faces a series of challenges. Thereby, research on recommendation system is of most realistic significance.Adopting the double clustering recommendation technique and based on user's rating history, the resource recommendation system of Educational Resource Network recommends what user is likely interested in for user, and implements the function of individual resource recommendation. When user searches something in large numbers of resource, the function gives a convenient and fast way.Firstly, this thesis introduces the general situation of recommendation system. Secondly, this thesis introduces the classification, structure, the flow of work and the recommendation technique of recommendation systems in detail. Finally, according to the introduction above, the thesis describes the concrete design and implementation of resource recommendation in Educational Resource Network.The main contribution of this thesis is that we propose a collaborative filtering recommendation algorithm based on double clustering. This approach first respectively clusters resources and users by the users' rating on items, then makes a collaborative filtering recommendation based on the clustering result. The new algorithm can shorten on-line recommendation time. Then, we apply the classical formula of cosine correlation to double clustering algorithm, leaving out the standardization operation. In the end, we implement an educational resource recommender system according to the need of the actual project and the result is positive.