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: "deleting edges to restrict the size of an epidemic in temporal networks"
  Abstract: A variety of potentially disease-spreading contact networks can be naturally modeled with graphs whose structure is subject to discrete changes over time, i.e. with temporal graphs. In such a temporal graph, vertices represent meaningful entities (such as animals or farms) and edges represent potentially infectious contacts between those entities. Furthermore the `availability' of an edge $e$ at time $t$ means that, at time $t$, the entities at the endpoints of $e$ are in contact. In this paper, motivated by network epidemiology applications in the dynamics of disease spreading on a data-derived network, we study the problem of deleting edges and/or edge availabilities from a given temporal graph in order to reduce its (temporal) connectivity. In particular, our aim is to find a temporal subgraph, in which the potential disease of any vertex $u$ can be transferred to only a limited number of other vertices $v$ using a temporal path (i.e. a path from $u$ to $v$, along which the times of the edge availabilities increase). We introduce two natural deletion problems for temporal graphs (for deletion of edges and of edge availabilities, respectively) and we provide positive and negative results on their computational complexity, both in the traditional and the parameterized sense, subject to various natural parameters.

Connected through hyperedge HE-1 (induced by source paper "distributed computation and reconfiguration in actively dynamic networks"):
  with members:
    - "on the transformation capability of feasible mechanisms for programmable matter"
    - "temporal network optimization subject to connectivity constraints"
    - "connectivity preserving network transformers"
    - "simple and efficient local codes for distributed stable network construction"
    - "naming and counting in anonymous unknown dynamic networks"
    - "the computational power of population protocols"

Connected through hyperedge HE-2 (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"
    - "stream graphs and link streams for the modeling of interactions over time"

Connected through hyperedge HE-3 (induced by source paper "how fast can we reach a target vertex in stochastic temporal graphs"):
  with members:
    - "temporal vertex cover with a sliding time window"
    - "sliding window temporal graph coloring"
    - "cover time in edge uniform stochastically evolving graphs"
    - "adapting the bron kerbosch algorithm for enumerating maximal cliques in temporal graphs"
    - "computing maximal cliques in link streams"
    - "temporal network optimization subject to connectivity constraints"
    - "on temporal graph exploration"
    - "dmvp foremost waypoint coverage of time varying graphs"

Connected through hyperedge HE-4 (induced by source paper "sliding window temporal graph coloring"):
  with members:
    - "temporal graph classes a view through temporal separators"
    - "listing all maximal k plexes in temporal graphs"
    - "stream graphs and link streams for the modeling of interactions over time"
    - "the complexity of finding small separators in temporal graphs"
    - "adapting the bron kerbosch algorithm for enumerating maximal cliques in temporal graphs"
    - "an introduction to temporal graphs an algorithmic perspective"
    - "computing maximal cliques in link streams"
    - "on temporal graph exploration"

Connected through hyperedge HE-5 (induced by source paper "changing times to minimise reachability in temporal graphs"):
  with members:
    - "the computational complexity of finding separators in temporal graphs"
    - "adapting the bron kerbosch algorithm for enumerating maximal cliques in temporal graphs"
    - "survivability in time varying networks"
    - "deleting edges to restrict the size of an epidemic a new application for treewidth"
    - "an introduction to temporal graphs an algorithmic perspective"
    - "temporal network optimization subject to connectivity constraints"

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)