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: "faster algorithms for computing maximal 2 connected subgraphs in sparse directed graphs"
  Abstract: Connectivity related concepts are of fundamental interest in graph theory. The area has received extensive attention over four decades, but many problems remain unsolved, especially for directed graphs. A directed graph is 2-edge-connected (resp., 2-vertex-connected) if the removal of any edge (resp., vertex) leaves the graph strongly connected. In this paper we present improved algorithms for computing the maximal 2-edge- and 2-vertex-connected subgraphs of a given directed graph. These problems were first studied more than 35 years ago, with $\widetilde{O}(mn)$ time algorithms for graphs with m edges and n vertices being known since the late 1980s. In contrast, the same problems for undirected graphs are known to be solvable in linear time. Henzinger et al. [ICALP 2015] recently introduced $O(n^2)$ time algorithms for the directed case, thus improving the running times for dense graphs. Our new algorithms run in time $O(m^{3/2})$, which further improves the running times for sparse graphs. #R##N#The notion of 2-connectivity naturally generalizes to k-connectivity for $k>2$. For constant values of k, we extend one of our algorithms to compute the maximal k-edge-connected in time $O(m^{3/2} \log{n})$, improving again for sparse graphs the best known algorithm by Henzinger et al. [ICALP 2015] that runs in $O(n^2 \log n)$ time.

Connected through hyperedge HE-1 (induced by source paper "deterministic graph cuts in subquadratic time sparse balanced and k vertex"):
  with members:
    - "a faster local algorithm for detecting bounded size cuts with applications to higher connectivity problems"
    - "computing and testing small vertex connectivity in near linear time and queries"
    - "a deterministic algorithm for balanced cut with applications to dynamic connectivity flows and beyond"
    - "distributed edge connectivity in sublinear time"
    - "breaking quadratic time for small vertex connectivity and an approximation scheme"
    - "graph sketching against adaptive adversaries applied to the minimum degree algorithm"
    - "expander decomposition and pruning faster stronger and simpler"
    - "local flow partitioning for faster edge connectivity"

Connected through hyperedge HE-2 (induced by source paper "computing and testing small connectivity in near linear time and queries via fast local cut algorithms"):
  with members:
    - "a faster local algorithm for detecting bounded size cuts with applications to higher connectivity problems"
    - "computing and testing small vertex connectivity in near linear time and queries"
    - "breaking quadratic time for small vertex connectivity and an approximation scheme"
    - "a new algorithm for decremental single source shortest paths with applications to vertex capacitated flow and cut problems"
    - "expander decomposition and pruning faster stronger and simpler"
    - "on sampling edges almost uniformly"
    - "local flow partitioning for faster edge connectivity"
    - "on fully dynamic graph sparsifiers"

Connected through hyperedge HE-3 (induced by source paper "a faster local algorithm for detecting bounded size cuts with applications to higher connectivity problems"):
  with members:
    - "breaking quadratic time for small vertex connectivity and an approximation scheme"
    - "local flow partitioning for faster edge connectivity"
    - "on fully dynamic graph sparsifiers"
    - "powers of tensors and fast matrix multiplication"
    - "deterministic edge connectivity in near linear time"
    - "distributed computation of large scale graph problems"
    - "fast local computation algorithms"
    - "minimum cuts in near linear time"

Connected through hyperedge HE-4 (induced by source paper "computing and testing small vertex connectivity in near linear time and queries"):
  with members:
    - "a faster local algorithm for detecting bounded size cuts with applications to higher connectivity problems"
    - "breaking quadratic time for small vertex connectivity and an approximation scheme"
    - "a new algorithm for decremental single source shortest paths with applications to vertex capacitated flow and cut problems"
    - "distributed connectivity decomposition"

Connected through hyperedge HE-5 (induced by source paper "decremental single source reachability in planar digraphs"):
  with members:
    - "improved bounds for shortest paths in dense distance graphs"
    - "fully dynamic maximal matching in constant update time"
    - "popular conjectures as a barrier for dynamic planar graph algorithms"
    - "finding 2 edge and 2 vertex strongly connected components in quadratic time"
    - "improved algorithms for decremental single source reachability on directed graphs"
    - "sublinear time decremental algorithms for single source reachability and shortest paths on directed graphs"
    - "popular conjectures imply strong lower bounds for dynamic problems"
    - "optimal decremental connectivity in planar graphs"

Connected through hyperedge HE-6 (induced by source paper "contracting a planar graph efficiently"):
  with members:
    - "optimal decremental connectivity in planar graphs"
    - "structured recursive separator decompositions for planar graphs in linear time"

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)