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: "the linear arrangement problem parameterized above guaranteed value"
  Abstract: A linear arrangement (LA) is an assignment of distinct integers to the vertices of a graph. The cost of an LA is the sum of lengths of the edges of the graph, where the length of an edge is defined as the absolute value of the difference of the integers assigned to its ends. For many application one hopes to find an LA with small cost. However, it is a classical NP-complete problem to decide whether a given graph $G$ admits an LA of cost bounded by a given integer. Since every edge of $G$ contributes at least one to the cost of any LA, the problem becomes trivially fixed-parameter tractable (FPT) if parameterized by the upper bound of the cost. Fernau asked whether the problem remains FPT if parameterized by the upper bound of the cost minus the number of edges of the given graph; thus whether the problem is FPT ``parameterized above guaranteed value.'' We answer this question positively by deriving an algorithm which decides in time $O(m+n+5.88^k)$ whether a given graph with $m$ edges and $n$ vertices admits an LA of cost at most $m+k$ (the algorithm computes such an LA if it exists). Our algorithm is based on a procedure which generates a problem kernel of linear size in linear time for a connected graph $G$. We also prove that more general parameterized LA problems stated by Serna and Thilikos are not FPT, unless P=NP.

Connected through hyperedge HE-1 (induced by source paper "multidimensional binary vector assignment problem standard structural and above guarantee parameterizations"):
  with members:
    - "slightly superexponential parameterized problems"
    - "kernelization lower bounds by cross composition"
    - "faster parameterized algorithms using linear programming"
    - "constraint satisfaction problems parameterized above or below tight bounds a survey"
    - "on multiway cut parameterized above lower bounds"

Connected through hyperedge HE-2 (induced by source paper "parameterized and approximation algorithms for the load coloring problem"):
  with members:
    - "parameterized algorithms for load coloring problem"
    - "fixed parameter complexity of minimum profile problems"

Connected through hyperedge HE-3 (induced by source paper "note on maximal bisection above tight lower bound"):
  with members:
    - "vertex cover problem parameterized above and below tight bounds"
    - "betweenness parameterized above tight lower bound"
    - "a probabilistic approach to problems parameterized above or below tight bounds"
    - "solving max r sat above a tight lower bound"
    - "note on max lin 2 above average"
    - "kernel s for problems with no kernel on out trees with many leaves"
    - "fixed parameter complexity of minimum profile problems"

Connected through hyperedge HE-4 (induced by source paper "all ternary permutation constraint satisfaction problems parameterized above average have kernels with quadratic numbers of variables"):
  with members:
    - "vertex cover problem parameterized above and below tight bounds"
    - "betweenness parameterized above tight lower bound"
    - "a probabilistic approach to problems parameterized above or below tight bounds"
    - "solving max r sat above a tight lower bound"
    - "note on max lin 2 above average"
    - "fixed parameter complexity of minimum profile problems"

Connected through hyperedge HE-5 (induced by source paper "betweenness parameterized above tight lower bound"):
  with members:
    - "all ternary permutation constraint satisfaction problems parameterized above average have kernels with quadratic numbers of variables"
    - "a probabilistic approach to problems parameterized above or below tight bounds"
    - "approximation schemes for the betweenness problem in tournaments and related ranking problems"
    - "solving max r sat above a tight lower bound"
    - "note on max lin 2 above average"
    - "fixed parameter complexity of minimum profile problems"

Connected through hyperedge HE-6 (induced by source paper "a probabilistic approach to problems parameterized above or below tight bounds"):
  with members:
    - "all ternary permutation constraint satisfaction problems parameterized above average have kernels with quadratic numbers of variables"
    - "systems of linear equations over mathbb f _2 and problems parameterized above average"
    - "betweenness parameterized above tight lower bound"
    - "solving max r sat above a tight lower bound"
    - "note on max lin 2 above average"
    - "fixed parameter complexity of minimum profile problems"

Connected through hyperedge HE-7 (induced by source paper "solving max r sat above a tight lower bound"):
  with members:
    - "systems of linear equations over mathbb f _2 and problems parameterized above average"
    - "betweenness parameterized above tight lower bound"
    - "a probabilistic approach to problems parameterized above or below tight bounds"
    - "a new upper bound for max 2 sat a graph theoretic approach"
    - "fixed parameter complexity of minimum profile problems"

Connected through hyperedge HE-8 (induced by source paper "note on max lin 2 above average"):
  with members:
    - "a probabilistic approach to problems parameterized above or below tight bounds"
    - "solving max r sat above a tight lower bound"
    - "fixed parameter complexity of minimum profile problems"

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)