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: "efficient and adaptive parameterized algorithms on modular decompositions"
  Abstract: We study the influence of a graph parameter called modular-width on the time complexity for optimally solving well-known polynomial problems such as Maximum Matching, Triangle Counting, and Maximum $s$-$t$ Vertex-Capacitated Flow. The modular-width of a graph depends on its (unique) modular decomposition tree, and can be computed in linear time $O(n+m)$ for graphs with $n$ vertices and $m$ edges. Modular decompositions are an important tool for graph algorithms, e.g., for linear-time recognition of certain graph classes. Throughout, we obtain efficient parameterized algorithms of running times $O(f(mw)n+m)$, $O(n+f(mw)m)$ , or $O(f(mw)+n+m)$ for graphs of modular-width $mw$. Our algorithm for Maximum Matching, running in time $O(mw^2\log mw \cdot n+m)$, is both faster and simpler than the recent $O(mw^4n+m)$ time algorithm of Coudert et al. (SODA 2018). For several other problems, e.g., Triangle Counting and Maximum $b$-Matching, we give adaptive algorithms, meaning that their running times match the best unparameterized algorithms for worst-case modular-width of $mw=\Theta(n)$ and they outperform them already for $mw=o(n)$, until reaching linear time for $mw=O(1)$.

Connected through hyperedge HE-1 (induced by source paper "efficient parameterized algorithms for computing all pairs shortest paths"):
  with members:
    - "faster all pairs shortest paths via circuit complexity"
    - "a combinatorial algorithm for all pairs shortest paths in directed vertex weighted graphs with applications to disc graphs"

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"
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"

Connected through hyperedge HE-3 (induced by source paper "on adaptive algorithms for maximum matching"):
  with members:
    - "a quasi linear time b matching algorithm on distance hereditary graphs and bounded split width graphs"
    - "parameterized aspects of triangle enumeration"
    - "robust and adaptive search"
    - "on the power of tree depth for fully polynomial fpt algorithms"
    - "simplified algorithmic metatheorems beyond mso treewidth and neighborhood diversity"
    - "a linear time algorithm for maximum cardinality matching on cocomparability graphs"
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"
    - "navigating central path with electrical flows from flows to matchings and back"

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"
    - "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"
    - "when can graph hyperbolicity be computed in linear time"

Connected through hyperedge HE-5 (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"
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"
    - "on the power of tree depth for fully polynomial fpt algorithms"
    - "fully polynomial time parameterized computations for graphs and matrices of low treewidth"
    - "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-6 (induced by source paper "fully polynomial fpt algorithms for some classes of bounded clique width graphs"):
  with members:
    - "the use of a pruned modular decomposition for maximum matching algorithms on some graph classes"
    - "parameterized aspects of triangle enumeration"
    - "on the power of tree depth for fully polynomial fpt algorithms"
    - "when can graph hyperbolicity be computed in linear time"
    - "the power of data reduction for matching"
    - "tight hardness results for distance and centrality problems in constant degree graphs"
    - "fully polynomial time parameterized computations for graphs and matrices of low treewidth"
    - "polynomial fixed parameter algorithms a case study for longest path on interval graphs"

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)