A collaborative tagging system for learning resources sharing

Web 2.0 has an architecture for participation and sharing, thus encouraging users to add value to an application. This study proposes a refined Collaborative Content Sharing Module that better equips the LCMS to enhance the user experience on content sharing. Within this module, a concept space that brings both functions of tag recommendation and concept based search is generated using the alliance between tags and learning contents. The refined Related Tag Generator provides related tags to users, enabling them to determine whether to use precise tags (lower-level concepts) or fuzzy tags (upper-level concepts). Moreover, the refined Query Analyzer and Ranking algorithm can improve the recall of search results by using concept distance. Additionally, the navigation service is enhanced through a Topic Map generated by the concept space. An experiment is performed, demonstrating that the proposed system increases the recall of research results by 141% on average, with an average loss of precision of only 6% as the tradeoff. With this collaborative tagging system, users can better organize and more efficiently discover the required data in the resource sharing environment. The virtuous cycle of reuse and sharing is likely to increase the diversity of learning resources in the very near future.