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: "sorting searching and simulation in the mapreduce framework"
  Abstract: In this paper, we study the MapReduce framework from an algorithmic standpoint and demonstrate the usefulness of our approach by designing and analyzing efficient MapReduce algorithms for fundamental sorting, searching, and simulation problems. This study is motivated by a goal of ultimately putting the MapReduce framework on an equal theoretical footing with the well-known PRAM and BSP parallel models, which would benefit both the theory and practice of MapReduce algorithms. We describe efficient MapReduce algorithms for sorting, multi-searching, and simulations of parallel algorithms specified in the BSP and CRCW PRAM models. We also provide some applications of these results to problems in parallel computational geometry for the MapReduce framework, which result in efficient MapReduce algorithms for sorting, 2- and 3-dimensional convex hulls, and fixed-dimensional linear programming. For the case when mappers and reducers have a memory/message-I/O size of $M=\Theta(N^\epsilon)$, for a small constant $\epsilon>0$, all of our MapReduce algorithms for these applications run in a constant number of rounds.

Connected through hyperedge HE-1 (induced by source paper "equivalence classes and conditional hardness in massively parallel computations"):
  with members:
    - "walking randomly massively and efficiently"
    - "log diameter rounds algorithms for 2 vertex and 2 edge connectivity"
    - "dynamic algorithms for the massively parallel computation model"
    - "a conditional lower bound on graph connectivity in mapreduce"
    - "efficient circuit simulation in mapreduce"
    - "exponentially faster massively parallel maximal matching"
    - "parallel batch dynamic graphs algorithms and lower bounds"
    - "massively parallel algorithms for finding well connected components in sparse graphs"

Connected through hyperedge HE-2 (induced by source paper "parallel algorithms for small subgraph counting"):
  with members:
    - "log diameter rounds algorithms for 2 vertex and 2 edge connectivity"
    - "dynamic algorithms for the massively parallel computation model"
    - "linear time subgraph counting graph degeneracy and the chasm at size six"
    - "exponentially faster massively parallel maximal matching"
    - "faster algorithms for edge connectivity via random 2 out contractions"
    - "massively parallel algorithms for finding well connected components in sparse graphs"
    - "approximating edit distance in truly subquadratic time quantum and mapreduce"
    - "sparsifying distributed algorithms with ramifications in massively parallel computation and centralized local computation"

Connected through hyperedge HE-3 (induced by source paper "massively parallel algorithms for distance approximation and spanners"):
  with members:
    - "walking randomly massively and efficiently"
    - "dynamic algorithms for the massively parallel computation model"
    - "mapreduce meets fine grained complexity mapreduce algorithms for apsp matrix multiplication 3 sum and beyond"
    - "polylogarithmic time deterministic network decomposition and distributed derandomization"
    - "parallel approximate undirected shortest paths via low hop emulators"
    - "faster parallel algorithm for approximate shortest path"
    - "exponentially faster massively parallel maximal matching"
    - "faster algorithms for edge connectivity via random 2 out contractions"

Connected through hyperedge HE-4 (induced by source paper "new lower bounds for massively parallel computation from query complexity"):
  with members:
    - "walking randomly massively and efficiently"
    - "log diameter rounds algorithms for 2 vertex and 2 edge connectivity"
    - "exponentially faster massively parallel maximal matching"
    - "massively parallel algorithms for finding well connected components in sparse graphs"
    - "approximating edit distance in truly subquadratic time quantum and mapreduce"
    - "sparsifying distributed algorithms with ramifications in massively parallel computation and centralized local computation"
    - "weighted matchings via unweighted augmentations"
    - "round compression for parallel graph algorithms in strongly sublinear space"

Connected through hyperedge HE-5 (induced by source paper "batch dynamic algorithms via parallel change propagation and applications to dynamic trees"):
  with members:
    - "parallel batch dynamic graph connectivity"
    - "log diameter rounds algorithms for 2 vertex and 2 edge connectivity"
    - "dynamic algorithms for the massively parallel computation model"
    - "exponentially faster massively parallel maximal matching"
    - "parallel batch dynamic graphs algorithms and lower bounds"
    - "matching and mis for uniformly sparse graphs in the low memory mpc model"
    - "massively parallel algorithms for finding well connected components in sparse graphs"
    - "batch parallel euler tour trees"

Connected through hyperedge HE-6 (induced by source paper "how fast can you update your mst dynamic algorithms for cluster computing"):
  with members:
    - "parallel batch dynamic graph connectivity"
    - "dynamic algorithms for the massively parallel computation model"
    - "sparsifying distributed algorithms with ramifications in massively parallel computation and centralized local computation"
    - "mst in o 1 rounds of the congested clique"
    - "fast distributed algorithms for connectivity and mst in large graphs"
    - "almost optimal distributed algorithms for large scale graph problems"
    - "optimal deterministic routing and sorting on the congested clique"

Connected through hyperedge HE-7 (induced by source paper "connected components on a pram in log diameter time"):
  with members:
    - "massively parallel algorithms for finding well connected components in sparse graphs"
    - "robust massively parallel sorting"
    - "practical massively parallel sorting"
    - "communication steps for parallel query processing"

Connected through hyperedge HE-8 (induced by source paper "connecting mapreduce computations to realistic machine models"):
  with members:
    - "thrill high performance algorithmic distributed batch data processing with c"
    - "communication efficient algorithms for top k selection problems"
    - "bsp vs mapreduce"

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.DC(Distributed, Parallel, and Cluster Computing)