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: "on the discovery of success trajectories of authors"
  Abstract: Understanding the qualitative patterns of research endeavor of scientific authors in terms of publication count and their impact (citation) is important in order to quantify success trajectories. Here, we examine the career profile of authors in computer science and physics domains and discover at least six different success trajectories in terms of normalized citation count in longitudinal scale. Initial observations of individual trajectories lead us to characterize the authors in each category. We further leverage this trajectory information to build a two-stage stratification model to predict future success of an author at the early stage of her career. Our model outperforms the baseline with an average improvement of 15.68% for both the datasets.

Connected through hyperedge HE-1 (induced by source paper "c 3 index a pagerank based multi faceted metric for authors performance measurement"):
  with members:
    - "do pagerank based author rankings outperform simple citation counts"
    - "applying weighted pagerank to author citation networks"
    - "are researchers that collaborate more at the international level top performers an investigation on the italian university system"
    - "the inconsistency of the h index"
    - "pagerank for ranking authors in co citation networks"
    - "applying centrality measures to impact analysis a coauthorship network analysis"
    - "popular and or prestigious measures of scholarly esteem"

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)