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: "fully polynomial time parameterized computations for graphs and matrices of low treewidth"
  Abstract: We investigate the complexity of several fundamental polynomial-time solvable problems on graphs and on matrices, when the given instance has low treewidth; in the case of matrices, we consider the treewidth of the graph formed by non-zero entries. In each of the considered cases, the best known algorithms working on general graphs run in polynomial time, however the exponent of the polynomial is large. Therefore, our main goal is to construct algorithms with running time of the form $\textrm{poly}(k)\cdot n$ or $\textrm{poly}(k)\cdot n\log n$, where $k$ is the width of the tree decomposition given on the input. Such procedures would outperform the best known algorithms for the considered problems already for moderate values of the treewidth, like $O(n^{1/c})$ for some small constant $c$. #R##N#Our results include: #R##N#-- an algorithm for computing the determinant and the rank of an $n\times n$ matrix using $O(k^3\cdot n)$ time and arithmetic operations; #R##N#-- an algorithm for solving a system of linear equations using $O(k^3\cdot n)$ time and arithmetic operations; #R##N#-- an $O(k^3\cdot n\log n)$-time randomized algorithm for finding the cardinality of a maximum matching in a graph; #R##N#-- an $O(k^4\cdot n\log^2 n)$-time randomized algorithm for constructing a maximum matching in a graph; #R##N#-- an $O(k^2\cdot n\log n)$-time algorithm for finding a maximum vertex flow in a directed graph. #R##N#Moreover, we give an approximation algorithm for treewidth with time complexity suited to the running times as above. Namely, the algorithm, when given a graph $G$ and integer $k$, runs in time $O(k^7\cdot n\log n)$ and either correctly reports that the treewidth of $G$ is larger than $k$, or constructs a tree decomposition of $G$ of width $O(k^2)$.

Connected through hyperedge HE-1 (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"
    - "minimum cut of directed planar graphs in o nloglogn time"

Connected through hyperedge HE-2 (induced by source paper "computing maximum matchings in temporal graphs"):
  with members:
    - "temporal matching"
    - "how fast can we reach a target vertex in stochastic temporal graphs"
    - "fixed parameter algorithms for maximum profit facility location under matroid constraints"
    - "tight competitive ratios of classic matching algorithms in the fully online model"
    - "temporal vertex cover with a sliding time window"
    - "how to match when all vertices arrive online"
    - "sliding window temporal graph coloring"
    - "efficient and adaptive parameterized algorithms on modular decompositions"

Connected through hyperedge HE-3 (induced by source paper "temporal matching"):
  with members:
    - "stream graphs and link streams for the modeling of interactions over time"
    - "on the power of advice and randomization for online bipartite matching"
    - "computing maximal cliques in link streams"

Connected through hyperedge HE-4 (induced by source paper "parameterized complexity of diameter"):
  with members:
    - "towards improving brandes algorithm for betweenness centrality"
    - "towards tight approximation bounds for graph diameter and eccentricities"
    - "data reduction for maximum matching on real world graphs theory and experiments"
    - "multivariate analysis of orthogonal range searching and graph distances parameterized by treewidth"
    - "efficient and adaptive parameterized algorithms on modular decompositions"
    - "parameterized aspects of triangle enumeration"
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"
    - "voronoi diagrams on planar graphs and computing the diameter in deterministic tilde o n 5 3 time"

Connected through hyperedge HE-5 (induced by source paper "clustering to given connectivities"):
  with members:
    - "reducing cmso model checking to highly connected graphs"
    - "parameterized algorithms for partitioning graphs into highly connected clusters"
    - "clustering with local restrictions"
    - "finding connected secluded subgraphs"
    - "spanning circuits in regular matroids"
    - "parameterized algorithms for min max multiway cut and list digraph homomorphism"
    - "a short survey on data clustering algorithms"
    - "designing fpt algorithms for cut problems using randomized contractions"

Connected through hyperedge HE-6 (induced by source paper "a quasi linear time b matching algorithm on distance hereditary graphs and bounded split width graphs"):
  with members:
    - "parameterized aspects of triangle enumeration"
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"
    - "the weighted matching approach to maximum cardinality matching"
    - "on the power of tree depth for fully polynomial fpt algorithms"
    - "when can graph hyperbolicity be computed in linear time"
    - "a linear time algorithm for maximum cardinality matching on cocomparability graphs"
    - "data structures for weighted matching and extensions to b matching and f factors"
    - "linear time split decomposition revisited"

Connected through hyperedge HE-7 (induced by source paper "data reduction for maximum matching on real world graphs theory and experiments"):
  with members:
    - "an adaptive version of brandes algorithm for betweenness centrality"
    - "on adaptive algorithms for maximum matching"
    - "wegotyoucovered the winning solver from the pace 2019 implementation challenge vertex cover track"
    - "efficient and adaptive parameterized algorithms on modular decompositions"
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"
    - "on the power of tree depth for fully polynomial fpt algorithms"
    - "polynomial fixed parameter algorithms a case study for longest path on interval graphs"
    - "scaling algorithms for weighted matching in general graphs"

Connected through hyperedge HE-8 (induced by source paper "the use of a pruned modular decomposition for maximum matching algorithms on some graph classes"):
  with members:
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"
    - "the weighted matching approach to maximum cardinality matching"
    - "a linear time algorithm for maximum cardinality matching on cocomparability graphs"
    - "algorithms parameterized by vertex cover and modular width through potential maximal cliques"
    - "parameterized algorithms for modular width"

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)