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: "cutting corners cheaply or how to remove steiner points"
  Abstract: Our main result is that the Steiner Point Removal (SPR) problem can always be solved with polylogarithmic distortion, which answers in the affirmative a question posed by Chan, Xia, Konjevod, and Richa (2006). Specifically, we prove that for every edge-weighted graph $G = (V,E,w)$ and a subset of terminals $T \subseteq V$, there is a graph $G'=(T,E',w')$ that is isomorphic to a minor of $G$, such that for every two terminals $u,v\in T$, the shortest-path distances between them in $G$ and in $G'$ satisfy $d_{G,w}(u,v) \le d_{G',w'}(u,v) \le O(\log^5|T|) \cdot d_{G,w}(u,v)$. Our existence proof actually gives a randomized polynomial-time algorithm. Our proof features a new variant of metric decomposition. It is well-known that every $n$-point metric space $(X,d)$ admits a $\beta$-separating decomposition for $\beta=O(\log n)$, which roughly means for every desired diameter bound $\Delta>0$ there is a randomized partitioning of $X$, which satisfies the following separation requirement: for every $x,y \in X$, the probability they lie in different clusters of the partition is at most $\beta\,d(x,y)/\Delta$. We introduce an additional requirement, which is the following tail bound: for every shortest-path $P$ of length $d(P) \leq \Delta/\beta$, the number of clusters of the partition that meet the path $P$, denoted $Z_P$, satisfies $\Pr[Z_P > t] \le 2e^{-\Omega(t)}$ for all $t>0$.

Connected through hyperedge HE-1 (induced by source paper "metric decompositions of path separable graphs"):
  with members:
    - "vertex sparsifiers new results from old techniques"
    - "cops robbers and threatening skeletons padded decomposition for minor free graphs"
    - "ramsey partitions and proximity data structures"
    - "measured descent a new embedding method for finite metrics"

Connected through hyperedge HE-2 (induced by source paper "vertex sparsifiers new results from old techniques"):
  with members:
    - "towards 1 epsilon approximate flow sparsifiers"
    - "approximation algorithms and hardness of the k route cut problem"
    - "metric extension operators vertex sparsifiers and lipschitz extendability"
    - "flow cut gaps for integer and fractional multiflows"
    - "interchanging distance and capacity in probabilistic mappings"

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)