human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "information resources in high energy physics surveying the present landscape and charting the future course"
  Abstract: Access to previous results is of paramount importance in the scientific process. Recent progress in information management focuses on building e-infrastructures for the optimization of the research workflow, through both policy-driven and user-pulled dynamics. For decades, High-Energy Physics (HEP) has pioneered innovative solutions in the field of information management and dissemination. In light of a transforming information environment, it is important to assess the current usage of information resources by researchers and HEP provides a unique test-bed for this assessment. A survey of about 10% of practitioners in the field reveals usage trends and information needs. Community-based services, such as the pioneering arXiv and SPIRES systems, largely answer the need of the scientists, with a limited but increasing fraction of younger users relying on Google. Commercial services offered by publishers or database vendors are essentially unused in the field. The survey offers an insight into the most important features that users require to optimize their research workflow. These results inform the future evolution of information management in HEP and, as these researchers are traditionally ``early adopters'' of innovation in scholarly communication, can inspire developments of disciplinary repositories serving other communities.

Connected through hyperedge HE-1 (induced by source paper "astrophysicists and physicists as creators of arxiv based commenting resources for their research communities an initial survey"):
  with members:
    - "scholarly use of social media and altmetrics a review of the literature"
    - "astrophysicists on twitter an in depth analysis of tweeting and scientific publication behavior"
    - "the potential of preprints to accelerate scholarly communication a bibliometric analysis based on selected journals"
    - "the convergence of digital libraries and the peer review process"

Connected through hyperedge HE-2 (induced by source paper "ethnicity sensitive author disambiguation using semi supervised learning"):
  with members:
    - "author name disambiguation by using deep neural network"
    - "exploiting citation networks for large scale author name disambiguation"
    - "api design for machine learning software experiences from the scikit learn project"
    - "separating the articles of authors with the same name"

Connected through hyperedge HE-3 (induced by source paper "citing and reading behaviours in high energy physics how a community stopped worrying about journals and learned to love repositories"):
  with members:
    - "innovation in scholarly communication vision and projects from high energy physics"
    - "author choice open access publishing in the biological and medical literature a citation analysis"
    - "does the arxiv lead to higher citations and reduced publisher downloads for mathematics articles"
    - "open access does not increase citations for research articles from the astrophysical journal"
    - "the effect of open access upon citation impact an analysis of arxiv s condensed matter section"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.DL(Digital Libraries)