human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "on the diameter of hyperbolic random graphs"):
  Abstract: For understanding the structure of the resulting graphs and for analyzing the behavior of network algorithms, the next question is bounding the size of the diameter. The only known bound is $$\mathcal {O}\log n^{32/3-\beta 5-\beta }$$ Kiwi and Mitsche. ANALCO, pp. 26---39, 2015. We present two much simpler proofs for an improved upper bound of $$\mathcal {O}\log n^{2/3-\beta }$$ and a lower bound of $$\Omega \log n$$. If the average degree is bounded from above by some constant, we show that the latter bound is tight by proving an upper bound of $$\mathcal {O}\log n$$ for the diameter.

Includes members:
  Member "network mapping by replaying hyperbolic growth":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "social centralization and semantic collapse hyperbolic embeddings of networks and text")
  Member "geometric inhomogeneous random graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "recent advances in scalable network generation")
  Member "fast generation of dynamic complex networks with underlying hyperbolic geometry":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "engineering parallel algorithms for community detection in massive networks")
  Member "general drift analysis with tail bounds":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sharp bounds on the runtime of the 1 1 ea via drift analysis and analytic combinatorial tools")
  Member "sustaining the internet with hyperbolic mapping":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hyperkg hyperbolic knowledge graph embeddings for knowledge base completion")

Question: Please tell me which class the source paper 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.DM(Discrete Mathematics)