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: "on the size and the approximability of minimum temporally connected subgraphs"
  Abstract: We consider temporal graphs with discrete time labels and investigate the size and the approximability of minimum temporally connected spanning subgraphs. We present a family of minimally connected temporal graphs with $n$ vertices and $\Omega(n^2)$ edges, thus resolving an open question of (Kempe, Kleinberg, Kumar, JCSS 64, 2002) about the existence of sparse temporal connectivity certificates. Next, we consider the problem of computing a minimum weight subset of temporal edges that preserve connectivity of a given temporal graph either from a given vertex r (r-MTC problem) or among all vertex pairs (MTC problem). We show that the approximability of r-MTC is closely related to the approximability of Directed Steiner Tree and that r-MTC can be solved in polynomial time if the underlying graph has bounded treewidth. We also show that the best approximation ratio for MTC is at least $O(2^{\log^{1-\epsilon} n})$ and at most $O(\min\{n^{1+\epsilon}, (\Delta M)^{2/3+\epsilon}\})$, for any constant $\epsilon > 0$, where $M$ is the number of temporal edges and $\Delta$ is the maximum degree of the underlying graph. Furthermore, we prove that the unweighted version of MTC is APX-hard and that MTC is efficiently solvable in trees and $2$-approximable in cycles.

Connected through hyperedge HE-1 (induced by source paper "the computational complexity of finding temporal paths under waiting time constraints"):
  with members:
    - "an adaptive version of brandes algorithm for betweenness centrality"
    - "efficient computation of optimal temporal walks under waiting time constraints"
    - "how fast can we reach a target vertex in stochastic temporal graphs"
    - "temporal cliques admit sparse spanners"
    - "fixed parameter algorithms for maximum profit facility location under matroid constraints"
    - "the temporal explorer who returns to the base"
    - "changing times to minimise reachability in temporal graphs"
    - "deleting edges to restrict the size of an epidemic in temporal networks"

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"
    - "efficient and adaptive parameterized algorithms on modular decompositions"

Connected through hyperedge HE-3 (induced by source paper "efficient computation of optimal temporal walks under waiting time constraints"):
  with members:
    - "multistage s t path confronting similarity with dissimilarity"
    - "the computational complexity of finding temporal paths under waiting time constraints"
    - "the complexity of finding small separators in temporal graphs"
    - "temporal network optimization subject to connectivity constraints"
    - "route planning in transportation networks"
    - "time varying graphs and dynamic networks"

Connected through hyperedge HE-4 (induced by source paper "temporal graph classes a view through temporal separators"):
  with members:
    - "the computational complexity of finding separators in temporal graphs"
    - "the complexity of finding small separators in temporal graphs"
    - "steiner network problems on temporal graphs"
    - "an introduction to temporal graphs an algorithmic perspective"
    - "on temporal graph exploration"
    - "time varying graphs and dynamic networks"

Connected through hyperedge HE-5 (induced by source paper "the complexity of finding small separators in temporal graphs"):
  with members:
    - "temporal vertex cover with a sliding time window"
    - "sliding window temporal graph coloring"
    - "listing all maximal k plexes in temporal graphs"
    - "cluster editing for multi layer and temporal graphs"
    - "stream graphs and link streams for the modeling of interactions over time"
    - "adapting the bron kerbosch algorithm for enumerating maximal cliques in temporal graphs"
    - "survivability in time varying networks"
    - "an introduction to temporal graphs an algorithmic perspective"

Connected through hyperedge HE-6 (induced by source paper "the computational complexity of finding separators in temporal graphs"):
  with members:
    - "temporal vertex cover with a sliding time window"
    - "temporal graph classes a view through temporal separators"
    - "adapting the bron kerbosch algorithm for enumerating maximal cliques in temporal graphs"
    - "survivability in time varying networks"
    - "time varying graphs and dynamic networks"

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)