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: "lossy kernels for connected dominating set on sparse graphs"
  Abstract: Given a graph $G$ and $k\in{\mathbb N}$, the Dominating Set problem asks for a subset $D$ of $k$ vertices such that every vertex in $G$ is either in $D$ or has a neighbor in $D$. It is well known that Dominating Set is ${\sf W}[2]$-hard when parameterized by $k$. But it admits a linear kernel on graphs of bounded expansion and a polynomial kernel on $K_{d,d}$-free graphs, for a fixed constant $d$. In contrast, the closely related Connected Dominating Set problem (where $G[D]$ is required to be connected) is known not to admit such kernels unless $\textsf{NP} \subseteq \textsf{coNP/poly}$. We show that even though the kernelization complexity of Dominating Set and Connected Dominating Set diverges on sparse graphs this divergence is not as extreme as kernelization lower bounds suggest. To do so, we study the Connected Dominating Set problem under the recently introduced framework of lossy kernelization. In this framework, for $\alpha>1$, an $\alpha$-approximate bikernel (kernel) is a polynomial-time algorithm that takes as input an instance $(I,k)$ and outputs an instance $(I',k')$ of a problem (the same problem) such that, for every $c > 1$, a $c$-approximate solution for the new instance can be turned into a $c\alpha$-approximate solution of the original instance in polynomial time. Moreover, the size of $(I',k')$ is bounded by a function of $k$ and $\alpha$. We show that Connected Dominating Set admits an $\alpha$-approximate bikernel on graphs of bounded expansion and an $\alpha$-approximate kernel on $K_{d,d}$-free graphs, for every $\alpha>1$. For $K_{d,d}$-free graphs we obtain instances of size $k^{\mathcal{O}(d^2 / (\alpha-1))}$ while for bounded expansion graphs we obtain instances of size $\mathcal{O}(f(\alpha) k)$ (i.e, linear in $k$), where $f(\alpha)$ is a computable function depending only on $\alpha$.

Connected through hyperedge HE-1 (induced by source paper "empirical evaluation of approximation algorithms for generalized graph coloring and uniform quasi wideness"):
  with members:
    - "exactly solving the maximum weight independent set problem on large real world graphs"
    - "experimental evaluation of kernelization algorithms to dominating set"
    - "polynomial bounds for centered colorings on proper minor closed graph classes"
    - "kernelization and approximation of distance r independent sets on nowhere dense graphs"
    - "distributed domination on graph classes of bounded expansion"
    - "reconfiguration on nowhere dense graph classes"
    - "positive instance driven dynamic programming for treewidth"
    - "experimental evaluation of counting subgraph isomorphisms in classes of bounded expansion"

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)