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: "new algorithms for maximum disjoint paths based on tree likeness"
  Abstract: We study the classical NP-hard problems of finding maximum-size subsets from given sets of $k$ terminal pairs that can be routed via edge-disjoint paths (MaxEDP) or node-disjoint paths (MaxNDP) in a given graph. The approximability of MaxEDP/NDP is currently not well understood; the best known lower bound is $\Omega(\log^{1/2-\epsilon}{n})$, assuming NP$~\not\subseteq~$ZPTIME$(n^{\mathrm{poly}\log n})$. This constitutes a significant gap to the best known approximation upper bound of $O(\sqrt{n})$ due to Chekuri et al. (2006) and closing this gap is currently one of the big open problems in approximation algorithms. In their seminal paper, Raghavan and Thompson (Combinatorica, 1987) introduce the technique of randomized rounding for LPs; their technique gives an $O(1)$-approximation when edges (or nodes) may be used by $O(\frac{\log n}{\log\log n})$ paths. #R##N#In this paper, we strengthen the above fundamental results. We provide new bounds formulated in terms of the feedback vertex set number $r$ of a graph, which measures its vertex deletion distance to a forest. In particular, we obtain the following. #R##N#* For MaxEDP, we give an $O(\sqrt{r}\cdot \log^{1.5}{kr})$-approximation algorithm. As $r\leq n$, up to logarithmic factors, our result strengthens the best known ratio $O(\sqrt{n})$ due to Chekuri et al. #R##N#* Further, we show how to route $\Omega(\mathrm{OPT})$ pairs with congestion $O(\frac{\log{kr}}{\log\log{kr}})$, strengthening the bound obtained by the classic approach of Raghavan and Thompson. #R##N#* For MaxNDP, we give an algorithm that gives the optimal answer in time $(k+r)^{O(r)}\cdot n$. If $r$ is at most triple-exponential in $k$, this improves the best known algorithm for MaxNDP with parameter $k$, by Kawarabayashi and Wollan (STOC 2010). #R##N#We complement these positive results by proving that MaxEDP is NP-hard even for $r=1$, and MaxNDP is W$[1]$-hard for parameter $r$.

Connected through hyperedge HE-1 (induced by source paper "the power of cut based parameters for computing edge disjoint paths"):
  with members:
    - "an fpt 2 approximation for tree cut decomposition"
    - "on structural parameterizations of the edge disjoint paths problem"
    - "on routing disjoint paths in bounded treewidth graphs"

Connected through hyperedge HE-2 (induced by source paper "improved approximation for node disjoint paths in grids with sources on the boundary"):
  with members:
    - "improved approximation for node disjoint paths in planar graphs"
    - "routing in undirected graphs with constant congestion"

Connected through hyperedge HE-3 (induced by source paper "walking through waypoints"):
  with members:
    - "virtual network embedding approximations leveraging randomized rounding"
    - "approximate and incremental network function placement"
    - "an approximation algorithm for path computation and function placement in sdns"
    - "service chain and virtual network embeddings approximations using randomized rounding"
    - "online admission control and embedding of service chains"
    - "on routing disjoint paths in bounded treewidth graphs"
    - "vertex disjoint path in upward planar graphs"
    - "the planar directed k vertex disjoint paths problem is fixed parameter tractable"

Connected through hyperedge HE-4 (induced by source paper "almost polynomial hardness of node disjoint paths in grids"):
  with members:
    - "improved approximation for node disjoint paths in grids with sources on the boundary"
    - "almost polynomial ratio eth hardness of approximating densest k subgraph"
    - "new hardness results for routing on disjoint paths"
    - "improved approximation for node disjoint paths in planar graphs"
    - "routing in undirected graphs with constant congestion"

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)