Fusion of motivational strategies with recommender system innovative framework for digital repositories

Digital Repositories are precisely intended to support information retrieval activities. They evolve to retain pace with novelty on the internet. Therefore, requires calibration in the architecture of such system. However, in endeavoring to deliver the best services, research must prominence on enhancing the motivational strategies and recommendation techniques to boost user participation and trust over the system. To attain this goal, the open learner model with the tag base recommender system is implemented. It narrows down the search space and empowers the users with the maximum level of trust and satisfaction. Developing countries are eager consumers of digital libraries but the unavailability of resources, not consigned to becoming “read-only cultures” in the digital revolution and out-of-focus directions cause the digital divide. This proposed framework combines new motivational approaches with the integration of the best features of Digital Libraries, educational systems, and widespread resource sharing systems. To influence the effectiveness, learnability and convenience of a system, particular characteristics are syndicated. Pioneering consultation platform, news feed and membership strategies contribute in inspiring the users towards the system. Hence, it also diminishes all the weaknesses and flaws that have been disclosed in earlier researches regarding Digital Repositories. In this paper, the design of enhanced framework is described briefly.