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 fpt algorithms for some classes of bounded clique width graphs"
  Abstract: Parameterized complexity theory has enabled a refined classification of the difficulty of NP-hard optimization problems on graphs with respect to key structural properties, and so to a better understanding of their true difficulties. More recently, hardness results for problems in P were achieved using reasonable complexity theoretic assumptions such as: Strong Exponential Time Hypothesis (SETH), 3SUM and All-Pairs Shortest-Paths (APSP). According to these assumptions, many graph theoretic problems do not admit truly subquadratic algorithms, nor even truly subcubic algorithms (Williams and Williams, FOCS 2010 and Abboud, Grandoni, Williams, SODA 2015). A central technique used to tackle the difficulty of the above mentioned problems is fixed-parameter algorithms for polynomial-time problems with polynomial dependency in the fixed parameter (P-FPT). This technique was introduced by Abboud, Williams and Wang in SODA 2016 and continued by Husfeldt (IPEC 2016) and Fomin et al. (SODA 2017), using the treewidth as a parameter. Applying this technique to clique-width, another important graph parameter, remained to be done. In this paper we study several graph theoretic problems for which hardness results exist such as cycle problems (triangle detection, triangle counting, girth, diameter), distance problems (diameter, eccentricities, Gromov hyperbolicity, betweenness centrality) and maximum matching. We provide hardness results and fully polynomial FPT algorithms, using clique-width and some of its upper-bounds as parameters (split-width, modular-width and $P\_4$-sparseness). We believe that our most important result is an ${\cal O}(k^4 \cdot n + m)$-time algorithm for computing a maximum matching where $k$ is either the modular-width or the $P\_4$-sparseness. The latter generalizes many algorithms that have been introduced so far for specific subclasses such as cographs, $P\_4$-lite graphs, $P\_4$-extendible graphs and $P\_4$-tidy graphs. Our algorithms are based on preprocessing methods using modular decomposition, split decomposition and primeval decomposition. Thus they can also be generalized to some graph classes with unbounded clique-width.

Connected through hyperedge HE-1 (induced by source paper "iterated type partitions"):
  with members:
    - "parameterized complexity of equitable coloring"
    - "target set selection in dense graph classes"
    - "evangelism in social networks algorithms and complexity"
    - "partitioning graphs into induced subgraphs"
    - "parameterized algorithms for modular width"
    - "using neighborhood diversity to solve hard problems"

Connected through hyperedge HE-2 (induced by source paper "b coloring parameterized by clique width"):
  with members:
    - "complexity of fall coloring for restricted graph classes"
    - "a complexity dichotomy for critical values of the b chromatic number of graphs"

Connected through hyperedge HE-3 (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-4 (induced by source paper "diameter computation on h minor free graphs and graphs of bounded distance vc dimension"):
  with members:
    - "planar diameter via metric compression"
    - "fast diameter computation within split graphs"
    - "solving linear programs in the current matrix multiplication time"
    - "towards tight approximation bounds for graph diameter and eccentricities"
    - "multivariate analysis of orthogonal range searching and graph distances parameterized by treewidth"
    - "voronoi diagrams on planar graphs and computing the diameter in deterministic tilde o n 5 3 time"
    - "subquadratic algorithms for the diameter and the sum of pairwise distances in planar graphs"
    - "on the hardness of partially dynamic graph problems and connections to diameter"

Connected through hyperedge HE-5 (induced by source paper "a story of diameter radius and helly property"):
  with members:
    - "diameter computation on h minor free graphs and graphs of bounded distance vc dimension"
    - "fast diameter computation within split graphs"
    - "multivariate analysis of orthogonal range searching and graph distances parameterized by treewidth"
    - "voronoi diagrams on planar graphs and computing the diameter in deterministic tilde o n 5 3 time"
    - "subquadratic algorithms for the diameter and the sum of pairwise distances in planar graphs"
    - "identifying codes in hereditary classes of graphs and vc dimension"
    - "covering nearly surface embedded graphs with a fixed number of balls"
    - "the covert set cover problem with application to network discovery"

Connected through hyperedge HE-6 (induced by source paper "fast approximation and exact computation of negative curvature parameters of graphs"):
  with members:
    - "effect of gromov hyperbolicity parameter on cuts and expansions in graphs and some algorithmic implications"
    - "when can graph hyperbolicity be computed in linear time"
    - "core congestion is inherent in hyperbolic networks"
    - "an improved combinatorial algorithm for boolean matrix multiplication"
    - "into the square on the complexity of quadratic time solvable problems"
    - "computing the gromov hyperbolicity of a discrete metric space"

Connected through hyperedge HE-7 (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"
    - "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-8 (induced by source paper "efficient and adaptive parameterized algorithms on modular decompositions"):
  with members:
    - "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"
    - "data structures for weighted matching and extensions to b matching and f factors"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"
    - "polynomial fixed parameter algorithms a case study for longest path on interval graphs"
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"

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)