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: "best of two local models local centralized and local distributed algorithms"
  Abstract: We consider two models of computation: local centralized algorithms and local distributed algorithms. Algorithms in one model are adapted to the other model to obtain improved algorithms. Distributed vertex coloring is employed to design improved local centralized algorithms for: maximal independent set, maximal matching, and an approximation scheme for maximum matching over bounded degree graphs. The improvement is threefold: the algorithms are deterministic, stateless, and the number of probes is poly(log ∗ n). The recursive local centralized improvement technique by Nguyen and Onak [NO08] is employed to obtain an improved distributed approximation scheme for maximum matching. The number of rounds of the distributed algorithm is O(log ∗ n) for bounded degree graphs.

Connected through hyperedge HE-1 (induced by source paper "sublinear random access generators for preferential attachment graphs"):
  with members:
    - "a scalable generative graph model with community structure"
    - "new techniques and tighter bounds for local computation algorithms"
    - "local algorithms for sparse spanning graphs"
    - "a local computation approximation scheme to maximum matching"
    - "converting online algorithms to local computation algorithms"
    - "space efficient local computation algorithms"
    - "a near optimal sublinear time algorithm for approximating the minimum vertex cover size"
    - "fast local computation algorithms"

Connected through hyperedge HE-2 (induced by source paper "local computation algorithms for graphs of non constant degrees"):
  with members:
    - "flow based algorithms for local graph clustering"
    - "distributed maximum matching in bounded degree graphs"
    - "new techniques and tighter bounds for local computation algorithms"
    - "local algorithms for sparse spanning graphs"
    - "a local computation approximation scheme to maximum matching"
    - "a simple online competitive adaptation of lempel ziv compression with efficient random access support"
    - "local computation mechanism design"
    - "the power of local information in social networks"

Connected through hyperedge HE-3 (induced by source paper "non local probes do not help with graph problems"):
  with members:
    - "distributed maximum matching in bounded degree graphs"
    - "new techniques and tighter bounds for local computation algorithms"
    - "local algorithms for sparse spanning graphs"
    - "large cuts with local algorithms on triangle free graphs"
    - "a local computation approximation scheme to maximum matching"
    - "converting online algorithms to local computation algorithms"
    - "local reconstructors and tolerant testers for connectivity and diameter"
    - "fast local computation algorithms"

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.DS(Data Structures and Algorithms)