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: "the h index of a graph and its application to dynamic subgraph statistics"
  Abstract: We describe a data structure that maintains the number of triangles in a dynamic undirected graph, subject to insertions and deletions of edges and of degree-zero vertices. More generally it can be used to maintain the number of copies of each possible three-vertex subgraph in time O(h) per update, where h is the h-index of the graph, the maximum number such that the graph contains $h$ vertices of degree at least h. We also show how to maintain the h-index itself, and a collection of h high-degree vertices in the graph, in constant time per update. Our data structure has applications in social network analysis using the exponential random graph model (ERGM); its bound of O(h) time per edge is never worse than the Theta(sqrt m) time per edge necessary to list all triangles in a static graph, and is strictly better for graphs obeying a power law degree distribution. In order to better understand the behavior of the h-index statistic and its implications for the performance of our algorithms, we also study the behavior of the h-index on a set of 136 real-world networks.

Connected through hyperedge HE-1 (induced by source paper "a systematic survey of general sparse matrix matrix multiplication"):
  with members:
    - "high performance sparse matrix matrix products on intel knl and multicore architectures"
    - "sparse matrix matrix multiplication on multilevel memory architectures algorithms and experiments"
    - "multi threaded sparse matrix matrix multiplication for many core and gpu architectures"
    - "porting of the dbcsr library for sparse matrix matrix multiplications to intel xeon phi systems"
    - "static graph challenge subgraph isomorphism"
    - "a comparative study on exact triangle counting algorithms on the gpu"
    - "hypergraph partitioning for sparse matrix matrix multiplication"
    - "locality aware parallel block sparse matrix matrix multiplication using the chunks and tasks programming model"

Connected through hyperedge HE-2 (induced by source paper "parameterized aspects of triangle enumeration"):
  with members:
    - "an adaptive version of brandes algorithm for betweenness centrality"
    - "data reduction for maximum matching on real world graphs theory and experiments"
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"
    - "kernelization lower bounds for finding constant size subgraphs"
    - "when can graph hyperbolicity be computed in linear time"
    - "fully polynomial time parameterized computations for graphs and matrices of low treewidth"
    - "polynomial fixed parameter algorithms a case study for longest path on interval graphs"
    - "joins via geometric resolutions worst case and beyond"

Connected through hyperedge HE-3 (induced by source paper "assessing the computational complexity of multi layer subgraph detection"):
  with members:
    - "stream graphs and link streams for the modeling of interactions over time"
    - "simultaneous feedback vertex set a parameterized perspective"
    - "an introduction to temporal graphs an algorithmic perspective"
    - "on the k anonymization of time varying and multi layer social graphs"
    - "the parameterized complexity of k biclique"
    - "towards optimal and expressive kernelization for d hitting set"
    - "clustering on multi layer graphs via subspace analysis on grassmann manifolds"
    - "clustering with multi layer graphs a spectral perspective"

Connected through hyperedge HE-4 (induced by source paper "fast quasi threshold editing"):
  with members:
    - "on the threshold of intractability"
    - "networkit an interactive tool suite for high performance network analysis"
    - "a polynomial kernel for trivially perfect editing"
    - "extended dynamic subgraph statistics using h index parameterized data structures"
    - "social structure of facebook networks"
    - "layered label propagation a multiresolution coordinate free ordering for compressing social networks"

Connected through hyperedge HE-5 (induced by source paper "win win kernelization for degree sequence completion problems"):
  with members:
    - "improved upper and lower bound heuristics for degree anonymization in social networks"
    - "editing to a connected graph of given degrees"
    - "editing to a graph of given degrees"
    - "kernelization lower bounds by cross composition"
    - "cross composition a new technique for kernelization lower bounds"
    - "a generalization of nemhauser and trotter s local optimization theorem"

Connected through hyperedge HE-6 (induced by source paper "ergms are hard"):
  with members:
    - "extended dynamic subgraph statistics using h index parameterized data structures"

Connected through hyperedge HE-7 (induced by source paper "on structural parameterizations for the 2 club problem"):
  with members:
    - "kernel bounds for structural parameterizations of pathwidth"
    - "on polynomial kernels for structural parameterizations of odd cycle transversal"

Connected through hyperedge HE-8 (induced by source paper "windows into relational events data structures for contiguous subsequences of edges"):
  with members:
    - "extended dynamic subgraph statistics using h index parameterized data structures"
    - "coevolution of network structure and content"
    - "betweenness centrality algorithms and lower bounds"
    - "fast approximation of centrality"

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)