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 "clustering to given connectivities"):
  Abstract: We define a general variant of the graph clustering problem where the criterion of density for the clusters is (high) connectivity. In {\sc Clustering to Given Connectivities}, we are given an $n$-vertex graph $G$, an integer $k$, and a sequence $\Lambda=\langle \lambda_{1},\ldots,\lambda_{t}\rangle$ of positive integers and we ask whether it is possible to remove at most $k$ edges from $G$ such that the resulting connected components are {\sl exactly} $t$ and their corresponding connectivities are lower-bounded by the numbers in $\Lambda$. We prove that this problem, parameterized by $k$, is fixed parameter tractable i.e., can be solved by an $f(k)\cdot n^{O(1)}$-step algorithm, for some function $f$ that depends only on the parameter $k$. Our algorithm uses the recursive understanding technique that is especially adapted so to deal with the fact that, in out setting, we do not impose any restriction to the connectivity demands in $\Lambda$. We also prove that {\sc Clustering to Given Connectivities}, parameterized by $k,$ does not admit a polynomial kernel unless NP$\subseteq$co-NP/poly.

Includes members:
  Member "reducing cmso model checking to highly connected graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hitting long directed cycles is fixed parameter tractable")
  Member "parameterized algorithms for partitioning graphs into highly connected clusters":
    also connected through other hyperedges:
      (none)
  Member "clustering with local restrictions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "randomized contractions meet lean decompositions")
  Member "finding connected secluded subgraphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "parameterized algorithms and data reduction for the short secluded s t path problem")
  Member "spanning circuits in regular matroids":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "covering vectors by spaces regular matroids")
  Member "fully polynomial time parameterized computations for graphs and matrices of low treewidth":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "minimum cuts in surface graphs")
  Member "parameterized algorithms for min max multiway cut and list digraph homomorphism":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the complexity of computing the k restricted edge connectivity of a graph")
  Member "a short survey on data clustering algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "cluster loss for person re identification")

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)