human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "network sparsification for steiner problems on planar and bounded genus graphs"):
  Abstract: We propose polynomial-time algorithms that sparsify planar and bounded-genus graphs while preserving optimal or near-optimal solutions to Steiner problems. Our main contribution is a polynomial-time algorithm that, given an unweighted graph $G$ embedded on a surface of genus $g$ and a designated face $f$ bounded by a simple cycle of length $k$, uncovers a set $F \subseteq E(G)$ of size polynomial in $g$ and $k$ that contains an optimal Steiner tree for any set of terminals that is a subset of the vertices of $f$. #R##N#We apply this general theorem to prove that: * given an unweighted graph $G$ embedded on a surface of genus $g$ and a terminal set $S \subseteq V(G)$, one can in polynomial time find a set $F \subseteq E(G)$ that contains an optimal Steiner tree $T$ for $S$ and that has size polynomial in $g$ and $|E(T)|$; * an analogous result holds for an optimal Steiner forest for a set $S$ of terminal pairs; * given an unweighted planar graph $G$ and a terminal set $S \subseteq V(G)$, one can in polynomial time find a set $F \subseteq E(G)$ that contains an optimal (edge) multiway cut $C$ separating $S$ and that has size polynomial in $|C|$. #R##N#In the language of parameterized complexity, these results imply the first polynomial kernels for Steiner Tree and Steiner Forest on planar and bounded-genus graphs (parameterized by the size of the tree and forest, respectively) and for (Edge) Multiway Cut on planar graphs (parameterized by the size of the cutset). Steiner Tree and similar "subset" problems were identified in [Demaine, Hajiaghayi, Computer J., 2008] as important to the quest to widen the reach of the theory of bidimensionality ([Demaine et al, JACM 2005], [Fomin et al, SODA 2010]). Therefore, our results can be seen as a leap forward to achieve this broader goal. #R##N#Additionally, we obtain a weighted variant of our main contribution.

Includes members:
  Member "a deterministic polynomial kernel for odd cycle transversal and vertex multiway cut in planar graphs":
    also connected through other hyperedges:
      (none)
  Member "improved guarantees for vertex sparsification in planar graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scattering and sparse partitions and their applications")
  Member "on subexponential parameterized algorithms for steiner tree and directed subset tsp on planar graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "tight bounds for planar strongly connected steiner subgraph with fixed number of terminals and extensions")
  Member "bidimensionality and kernels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hitting topological minors is fpt")
  Member "on problems as hard as cnf sat":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "an o 1 84 k parameterized algorithm for the multiterminal cut problem":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "shared memory branch and reduce for multiterminal cuts")
  Member "mimicking networks and succinct representations of terminal cuts":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "scattering and sparse partitions and their applications")
  Member "representative sets and irrelevant vertices new tools for kernelization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on quasipolynomial multicut mimicking networks and kernelization of multiway cut problems")

Question: Please tell me which class the source paper 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)