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: "deterministic edge connectivity in near linear time"
  Abstract: We present a deterministic near-linear time algorithm that computes the edge-connectivity and finds a minimum cut for a simple undirected unweighted graph G with n vertices and m edges. This is the first o(mn) time deterministic algorithm for the problem. In near-linear time we can also construct the classic cactus representation of all minimum cuts. #R##N#The previous fastest deterministic algorithm by Gabow from STOC'91 took ~O(m+k^2 n), where k is the edge connectivity, but k could be Omega(n). #R##N#At STOC'96 Karger presented a randomized near linear time Monte Carlo algorithm for the minimum cut problem. As he points out, there is no better way of certifying the minimality of the returned cut than to use Gabow's slower deterministic algorithm and compare sizes. #R##N#Our main technical contribution is a near-linear time algorithm that contract vertex sets of a simple input graph G with minimum degree d, producing a multigraph with ~O(m/d) edges which preserves all minimum cuts of G with at least 2 vertices on each side. #R##N#In our deterministic near-linear time algorithm, we will decompose the problem via low-conductance cuts found using PageRank a la Brin and Page (1998), as analyzed by Andersson, Chung, and Lang at FOCS'06. Normally such algorithms for low-conductance cuts are randomized Monte Carlo algorithms, because they rely on guessing a good start vertex. However, in our case, we have so much structure that no guessing is needed.

Connected through hyperedge HE-1 (induced by source paper "a deterministic algorithm for balanced cut with applications to dynamic connectivity flows and beyond"):
  with members:
    - "faster p norm minimizing flows via smoothed q norm problems"
    - "fast provably convergent irls algorithm for p norm linear regression"
    - "distributed edge connectivity in sublinear time"
    - "improved distributed expander decomposition and nearly optimal triangle enumeration"
    - "flows in almost linear time via adaptive preconditioning"
    - "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"
    - "graph sparsification spectral sketches and faster resistance computation via short cycle decompositions"

Connected through hyperedge HE-2 (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"
    - "faster algorithms for computing maximal 2 connected subgraphs in sparse directed graphs"

Connected through hyperedge HE-3 (induced by source paper "improved distributed expander decomposition and nearly optimal triangle enumeration"):
  with members:
    - "distributed edge connectivity in sublinear time"
    - "sparse matrix multiplication and triangle listing in the congested clique model"
    - "new distributed algorithms in almost mixing time via transformations from parallel algorithms"
    - "distributed triangle detection via expander decomposition"
    - "graph sparsification spectral sketches and faster resistance computation via short cycle decompositions"
    - "expander decomposition and pruning faster stronger and simpler"
    - "mst in o 1 rounds of the congested clique"
    - "fooling views a new lower bound technique for distributed computations under congestion"

Connected through hyperedge HE-4 (induced by source paper "minimum cuts in surface graphs"):
  with members:
    - "holiest minimum cost paths and flows in surface graphs"
    - "computational topology and the unique games conjecture"
    - "finding all useless arcs in directed planar graphs"
    - "local flow partitioning for faster edge connectivity"
    - "minor free graphs have light spanners"
    - "minimum cycle and homology bases of surface embedded graphs"
    - "recognizing weakly simple polygons"
    - "fully polynomial time parameterized computations for graphs and matrices of low treewidth"

Connected through hyperedge HE-5 (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"
    - "faster algorithms for computing maximal 2 connected subgraphs in sparse directed graphs"
    - "on sampling edges almost uniformly"
    - "local flow partitioning for faster edge connectivity"

Connected through hyperedge HE-6 (induced by source paper "a simple algorithm for minimum cuts in near linear time"):
  with members:
    - "distributed edge connectivity in sublinear time"
    - "faster algorithms for edge connectivity via random 2 out contractions"
    - "practical minimum cut algorithms"
    - "parallel minimum cuts in near linear work and low depth"
    - "local flow partitioning for faster edge connectivity"
    - "incremental exact min cut in poly logarithmic amortized update time"
    - "distributed minimum cut approximation"
    - "maintaining information in fully dynamic trees with top trees"

Connected through hyperedge HE-7 (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"
    - "faster algorithms for computing maximal 2 connected subgraphs in sparse directed graphs"
    - "local flow partitioning for faster edge connectivity"
    - "on fully dynamic graph sparsifiers"
    - "powers of tensors and fast matrix multiplication"
    - "distributed computation of large scale graph problems"
    - "fast local computation algorithms"
    - "minimum cuts in near linear time"

Connected through hyperedge HE-8 (induced by source paper "weighted min cut sequential cut query and streaming algorithms"):
  with members:
    - "polynomial pass lower bounds for graph streaming algorithms"
    - "a simple algorithm for minimum cuts in near linear time"
    - "faster algorithms for edge connectivity via random 2 out contractions"
    - "local flow partitioning for faster edge connectivity"
    - "computing exact minimum cuts without knowing the graph"
    - "single pass spectral sparsification in dynamic streams"
    - "single pass sparsification in the streaming model with edge deletions"
    - "minimum cuts in near 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)