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: "subgraph enumeration in massive graphs"
  Abstract: We consider the problem of enumerating all instances of a given pattern graph in a large data graph. Our focus is on determining the input/output (I/O) complexity of this problem. Let $E$ be the number of edges in the data graph, $k=O(1)$ be the number of vertices in the pattern graph, $B$ be the block length, and $M$ be the main memory size. The main results of the paper are two algorithms that enumerate all instances of the pattern graph. The first one is a deterministic algorithm that exploits a suitable independent set of the pattern graph of size $1\leq s \leq k/2$ and requires $O\left(E^{k-s}/\left(BM^{k-s-1}\right)\right)$ I/Os. The second algorithm is a randomized algorithm that enumerates all instances in $O\left(E^{k/2}/\left(BM^{k/2-1}\right)\right)$ expected I/Os; the same bound also applies with high probability under some assumptions. A lower bound shows that the deterministic algorithm is optimal for some pattern graphs with $s=k/2$ (e.g., paths and cycles of even length, meshes of even side), while the randomized algorithm is optimal for a wide class of pattern graphs, called Alon class (e.g., cliques, cycles and every graph with a perfect matching).

Connected through hyperedge HE-1 (induced by source paper "worst case optimal algorithms for parallel query processing"):
  with members:
    - "size bounds and query plans for relational joins"
    - "distributed computation of large scale graph problems"
    - "communication steps for parallel query processing"
    - "when distributed computation is communication expensive"

Connected through hyperedge HE-2 (induced by source paper "clique counting in mapreduce algorithms and experiments"):
  with members:
    - "the input output complexity of triangle enumeration"
    - "a novel approach to finding near cliques the triangle densest subgraph problem"
    - "enumerating subgraph instances using map reduce"
    - "space round tradeoffs for mapreduce computations"
    - "efficient triangle counting in large graphs via degree based vertex partitioning"
    - "sorting searching and simulation in the mapreduce framework"
    - "colorful triangle counting and a mapreduce implementation"

Connected through hyperedge HE-3 (induced by source paper "the input output complexity of triangle enumeration"):
  with members:
    - "the input output complexity of sparse matrix multiplication"
    - "why do simple algorithms for triangle enumeration work in the real world"
    - "3sum 3xor triangles"
    - "enumerating subgraph instances using map reduce"
    - "efficient triangle counting in large graphs via degree based vertex partitioning"

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)