human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "note on maximal bisection above tight lower bound"):
  Abstract: In a graph $G=(V,E)$, a bisection $(X,Y)$ is a partition of $V$ into sets $X$ and $Y$ such that $|X|\le |Y|\le |X|+1$. The size of $(X,Y)$ is the number of edges between $X$ and $Y$. In the Max Bisection problem we are given a graph $G=(V,E)$ and are required to find a bisection of maximum size. It is not hard to see that $\lceil |E|/2 \rceil$ is a tight lower bound on the maximum size of a bisection of $G$. We study parameterized complexity of the following parameterized problem called Max Bisection above Tight Lower Bound (Max-Bisec-ATLB): decide whether a graph $G=(V,E)$ has a bisection of size at least $\lceil |E|/2 \rceil+k,$ where $k$ is the parameter. We show that this parameterized problem has a kernel with $O(k^2)$ vertices and $O(k^3)$ edges, i.e., every instance of Max-Bisec-ATLB is equivalent to an instance of Max-Bisec-ATLB on a graph with at most $O(k^2)$ vertices and $O(k^3)$ edges.

Includes members:
  Member "vertex cover problem parameterized above and below tight bounds":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "domination above r independence does sparseness help")
  Member "betweenness parameterized above tight lower bound":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "satisfiability of ordering csps above average")
  Member "a probabilistic approach to problems parameterized above or below tight bounds":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hamiltonicity below dirac s condition")
  Member "solving max r sat above a tight lower bound":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "domination above r independence does sparseness help")
  Member "note on max lin 2 above average":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "constraint satisfaction problems parameterized above or below tight bounds a survey")
  Member "kernel s for problems with no kernel on out trees with many leaves":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a polynomial turing kernel for weighted independent set in bull free graphs")
  Member "fixed parameter complexity of minimum profile problems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "parameterized and approximation algorithms for the load coloring problem")
  Member "the linear arrangement problem parameterized above guaranteed value":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multidimensional binary vector assignment problem standard structural and above guarantee parameterizations")

Question: Please tell me which class the source paper 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)