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Abstract. Many industries face an increasing need for smart systems that support the processing and generation of digital content. This is both due to an ever increasing amount of incoming content that needs to be processed faster and more efficiently, but also due to an ever increasing pressure of publishing new content in cycles that are getting shorter and shorter. In a research and technology transfer project we develop a platform that provides content curation services that can be integrated into Content Management Systems, among others. In the project we develop curation services, which comprise semantic text and document analytics processes as well as knowledge technologies that can be applied to document collections. The key objective is to support digital curators in their daily work, i.e., to (semi-)automate processes that the human experts are normally required to carry out intellectually and, typically, without tool support. The goal is to enable knowledge workers to become more efficient and more effective as well as to produce high-quality content. In this article we focus on the current state of development with regard to semantic storytelling in our four use cases.

Based on the observation that the equation of state parameter ω can cross the phantom dividing ω = -1 and has a 99% probability of being ω < -1, we introduce an interaction between the modified Chaplygin gas and the barotropic background fluid. By studying the dynamical evolution of the MCG model with interaction and the statefinder diagnostic in autonomous system, we find that the MCG vacuum-energy-dominated phase is the only stable attractor, the universe evolves from the matter-dominated phase to the MCG vacuum-energy-dominated phase, and the effect of the transfer strength parameter c is evident. In addition, we have plotted the evolution trajectories of the interacting CG, GCG and MCG models with barotropic background fluid in the statefinder parameter (s - r)-plane to illustrate the discriminations among these scenarios.