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: "exact algorithms for maximum clique a computational study"
  Abstract: We investigate a number of recently reported exact algorithms for the maximum clique problem. The program code is presented and analyzed to show how small changes in implementation can have a drastic effect on performance. The computational study demonstrates how problem features and hardware platforms influence algorithm behaviour. The effect of vertex ordering is investigated. One of the algorithms (MCS) is broken into its constituent parts and we discover that one of these parts frequently degrades performance. It is shown that the standard procedure used for rescaling published results (i.e., adjusting run times based on the calibration of a standard program over a set of benchmarks) is unsafe and can lead to incorrect conclusions being drawn from empirical data.

Connected through hyperedge HE-1 (induced by source paper "replicable parallel branch and bound search"):
  with members:
    - "the shape of the search tree for the maximum clique problem and the implications for parallel branch and bound"
    - "exact algorithms for maximum clique a computational study"

Connected through hyperedge HE-2 (induced by source paper "fast algorithms for the maximum clique problem on massive graphs with applications to overlapping community detection"):
  with members:
    - "overlapping community detection in networks the state of the art and comparative study"
    - "exact algorithms for maximum clique a computational study"
    - "listing all maximal cliques in large sparse real world graphs"

Connected through hyperedge HE-3 (induced by source paper "coloring large complex networks"):
  with members:
    - "hop doubling label indexing for point to point distance querying on scale free networks"
    - "graph sample and hold a framework for big graph analytics"
    - "estimating clique composition and size distributions from sampled network data"
    - "graph cluster randomization network exposure to multiple universes"
    - "dimension reduction via colour refinement"
    - "subgraph frequencies mapping the empirical and extremal geography of large graph collections"
    - "network sampling from static to streaming graphs"
    - "exact algorithms for maximum clique a computational study"

Connected through hyperedge HE-4 (induced by source paper "a parallel branch and bound algorithm for the maximum labelled clique problem"):
  with members:
    - "the shape of the search tree for the maximum clique problem and the implications for parallel branch and bound"
    - "exact algorithms for maximum clique a computational study"

Connected through hyperedge HE-5 (induced by source paper "the shape of the search tree for the maximum clique problem and the implications for parallel branch and bound"):
  with members:
    - "greedy graph colouring is a misleading heuristic"
    - "exact algorithms for maximum clique a computational study"

Connected through hyperedge HE-6 (induced by source paper "empirical algorithmics draw your own conclusions"):
  with members:
    - "a bit parallel russian dolls search for a maximum cardinality clique in a graph"
    - "exact algorithms for maximum clique a computational study"

Connected through hyperedge HE-7 (induced by source paper "finding maximum k cliques faster using lazy global domination"):
  with members:
    - "exact algorithms for maximum clique a computational study"

Connected through hyperedge HE-8 (induced by source paper "a bit parallel russian dolls search for a maximum cardinality clique in a graph"):
  with members:
    - "exact algorithms for maximum clique a computational study"

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)