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: "improved upper and lower bound heuristics for degree anonymization in social networks"
  Abstract: Motivated by a strongly growing interest in anonymizing social network data, we investigate the NP-hard Degree Anonymization problem: given an undirected graph, the task is to add a minimum number of edges such that the graph becomes k-anonymous. That is, for each vertex there have to be at least k-1 other vertices of exactly the same degree. The model of degree anonymization has been introduced by Liu and Terzi [ACM SIGMOD'08], who also proposed and evaluated a two-phase heuristic. We present an enhancement of this heuristic, including new algorithms for each phase which significantly improve on the previously known theoretical and practical running times. Moreover, our algorithms are optimized for large-scale social networks and provide upper and lower bounds for the optimal solution. Notably, on about 26 % of the real-world data we provide (provably) optimal solutions; whereas in the other cases our upper bounds significantly improve on known heuristic solutions.

Connected through hyperedge HE-1 (induced by source paper "a parameterized algorithmics framework for degree sequence completion problems in directed graphs"):
  with members:
    - "graph editing to a given degree sequence"
    - "completing orientations of partially oriented graphs"
    - "win win kernelization for degree sequence completion problems"
    - "editing to a graph of given degrees"
    - "np hardness and fixed parameter tractability of realizing degree sequences with directed acyclic graphs"

Connected through hyperedge HE-2 (induced by source paper "a parameterized algorithmics framework for digraph degree sequence completion problems"):
  with members:
    - "graph editing to a given degree sequence"
    - "completing orientations of partially oriented graphs"
    - "win win kernelization for degree sequence completion problems"
    - "editing to a graph of given degrees"

Connected through hyperedge HE-3 (induced by source paper "parameterized algorithmics for graph modification problems on interactions with heuristics"):
  with members:
    - "win win kernelization for degree sequence completion problems"
    - "parameterized algorithmics for computational social choice nine research challenges"
    - "faster parameterized algorithms using linear programming"
    - "approximation and tidying a problem kernel for s plex cluster vertex deletion"

Connected through hyperedge HE-4 (induced by source paper "on the k anonymization of time varying and multi layer social graphs"):
  with members:
    - "keep your friends close and your facebook friends closer a multiplex network approach to the analysis of offline and online social ties"

Connected through hyperedge HE-5 (induced by source paper "win win kernelization for degree sequence completion problems"):
  with members:
    - "editing to a connected graph of given degrees"
    - "editing to a graph of given degrees"
    - "kernelization lower bounds by cross composition"
    - "the h index of a graph and its application to dynamic subgraph statistics"
    - "cross composition a new technique for kernelization lower bounds"
    - "a generalization of nemhauser and trotter s local optimization theorem"

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.SI(Social and Information Networks)