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: "external memory based distributed generation of massive scale social networks on small clusters"
  Abstract: Small distributed systems are limited by their main memory to generate massively large graphs. Trivial extension to current graph generators to utilize external memory leads to large amount of random I/O hence do not scale with size. In this work we offer a technique to generate massive scale graphs on small cluster of compute nodes with limited main memory. We develop several distributed and external memory algorithms, primarily, shuffle, relabel, redistribute, and, compressed-sparse-row (csr) convert. The algorithms are implemented in MPI/pthread model to help parallelize the operations across multicores within each core. Using our scheme it is feasible to generate a graph of size $2^{38}$ nodes (scale 38) using only 64 compute nodes. This can be compared with the current scheme would require at least 8192 compute node, assuming 64GB of main memory. #R##N#Our work has broader implications for external memory graph libraries such as STXXL and graph processing on SSD-based supercomputers such as Dash and Gordon [1][2].

Connected through hyperedge HE-1 (induced by source paper "large graph models a review"):
  with members:
    - "counting triangles in massive graphs with mapreduce"
    - "a scalable generative graph model with community structure"
    - "using triangles to improve community detection in directed networks"
    - "an in depth analysis of stochastic kronecker graphs"
    - "degree relations of triangles in real world networks and graph models"

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.DB(Databases)