Design And Implementation Of The Academic Resources Tagging Recommendation System Based On RDF

The Internet has changed our lives, but as more and more ordinary users to participate in the network, information resources are becoming increasingly complex. In the case of information overload, how to help users better search filtering and resources, it has become a major challenge. So socialization labels are widely used in personalization sites, that Folksonomy system. In this paper, academic resources as a background application is also on this issue has been studied, academic resources in the traditional sense may be the type of documents and other text, open classes and other resources are endless.From the user's point of view to add annotations to these resources, the label not only reflects the user's preference, it could imply semantic information resource itself can not be expressed, there is provided a unfettered, shareable new resource classification. Therefore, based on the tag search resources to improve the accuracy and breadth retrieved from a certain sense.The academic literature data storage uses RDF, a meta-data model for the description of Web resources, the foundation of the Semantic Web language, using triple to represent the relationship between the user, literature and label information, the use of RDF data model makes the system has better scalability, no need to change the table structure as the traditional database storage. Such as academic video site data collection can be applied to local and help build social networks distributed, interconnected across multiple sites RDF dataset. At the same time in an organization can interconnect different data sets, using SPARQL query language across data sets, were wandering in the RDF graph pattern, making it easy to find out the correlation between the information data. We will recommend for users of resources or other users may be interested combined with Folksonomy. In addition, this system also adding a certain element of community interaction, increase sharing between users, while providing an interface to an external call, we developed based on REST architecture API.The system uses a lightweight framework based on Python Flask development, to achieve the user for various types of academic resources management and labeling recommendation function, using tags to improve the retrieval quality of search-based. Using RDF store multiple data sources to achieve integration, so that the system has high reusability, scalability, etc., to provide users with a better user experience.