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: "flow cut gaps and face covers in planar graphs"
  Abstract: The relationship between the sparsest cut and the maximum concurrent multi-flow in graphs has been studied extensively. For general graphs with $k$ terminal pairs, the flow-cut gap is $O(\log k)$, and this is tight. But when topological restrictions are placed on the flow network, the situation is far less clear. In particular, it has been conjectured that the flow-cut gap in planar networks is $O(1)$, while the known bounds place the gap somewhere between $2$ (Lee and Raghavendra, 2003) and $O(\sqrt{\log k})$ (Rao, 1999). #R##N#A seminal result of Okamura and Seymour (1981) shows that when all the terminals of a planar network lie on a single face, the flow-cut gap is exactly $1$. This setting can be generalized by considering planar networks where the terminals lie on $\gamma>1$ faces in some fixed planar drawing. Lee and Sidiropoulos (2009) proved that the flow-cut gap is bounded by a function of $\gamma$, and Chekuri, Shepherd, and Weibel (2013) showed that the gap is at most $3\gamma$. We prove that the flow-cut gap is $O(\log\gamma)$, by showing that the edge-weighted shortest-path metric induced on the terminals admits a stochastic embedding into trees with distortion $O(\log\gamma)$, which is tight. #R##N#The preceding results refer to the setting of edge-capacitated networks. For vertex-capacitated networks, it can be significantly more challenging to control flow-cut gaps. While there is no exact vertex-capacitated version of the Okamura-Seymour Theorem, an approximate version holds; Lee, Mendel, and Moharrami (2015) showed that the vertex-capacitated flow-cut gap is $O(1)$ on planar networks whose terminals lie on a single face. We prove that the flow-cut gap is $O(\gamma)$ for vertex-capacitated instances when the terminals lie on at most $\gamma$ faces. In fact, this result holds in the more general setting of submodular vertex capacities.

Connected through hyperedge HE-1 (induced by source paper "scattering and sparse partitions and their applications"):
  with members:
    - "lossless prioritized embeddings"
    - "labelings vs embeddings on distributed representations of distances"
    - "on strong diameter padded decompositions"
    - "a face cover perspective to ell_1 embeddings of planar graphs"
    - "near isometric terminal embeddings for doubling metrics"
    - "light spanners for high dimensional norms via stochastic decompositions"
    - "steiner point removal with distortion o log k"
    - "improved guarantees for vertex sparsification in planar graphs"

Connected through hyperedge HE-2 (induced by source paper "network coding gaps for completion times of multiple unicasts"):
  with members:
    - "new distributed algorithms in almost mixing time via transformations from parallel algorithms"
    - "faster distributed shortest path approximations via shortcuts"
    - "lower bounds for external memory integer sorting via network coding"
    - "low congestion shortcuts without embedding"
    - "cops robbers and threatening skeletons padded decomposition for minor free graphs"
    - "simple fast and deterministic gossip and rumor spreading"
    - "lexicographic products and the power of non linear network coding"
    - "distributed verification and hardness of distributed approximation"

Connected through hyperedge HE-3 (induced by source paper "a face cover perspective to ell_1 embeddings of planar graphs"):
  with members:
    - "nearly eth tight algorithms for planar steiner tree with terminals on few faces"
    - "an exponential lower bound for cut sparsifiers in planar graphs"
    - "metric embedding via shortest path decompositions"
    - "refined vertex sparsifiers of planar graphs"
    - "on notions of distortion and an almost minimum spanning tree with constant average distortion"
    - "vertex sparsifiers new results from old techniques"
    - "cops robbers and threatening skeletons padded decomposition for minor free graphs"
    - "flow cut gaps for integer and fractional multiflows"

Connected through hyperedge HE-4 (induced by source paper "nearly eth tight algorithms for planar steiner tree with terminals on few faces"):
  with members:
    - "on subexponential parameterized algorithms for steiner tree and directed subset tsp on planar graphs"
    - "subexponential parameterized algorithms for planar and apex minor free graphs via low treewidth pattern covering"
    - "optimal parameterized algorithms for planar facility location problems using voronoi diagrams"
    - "approximation schemes for steiner forest on planar graphs and graphs of bounded treewidth"

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)