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 "temporal vertex cover with a sliding time window"):
  Abstract: Modern, inherently dynamic systems are usually characterized by a network structure, i.e. an underlying graph topology, which is subject to discrete changes over time. Given a static underlying graph $G$, a temporal graph can be represented via an assignment of a set of integer time-labels to every edge of $G$, indicating the discrete time steps when this edge is active. While most of the recent theoretical research on temporal graphs has focused on the notion of a temporal path and other "path-related" temporal notions, only few attempts have been made to investigate "non-path" temporal graph problems. In this paper, motivated by applications in sensor and in transportation networks, we introduce and study two natural temporal extensions of the classical problem VERTEX COVER. In our first problem, TEMPORAL VERTEX COVER, the aim is to cover every edge at least once during the lifetime of the temporal graph, where an edge can only be covered by one of its endpoints at a time step when it is active. In our second, more pragmatic variation SLIDING WINDOW TEMPORAL VERTEX COVER, we are also given a parameter $\Delta$, and our aim is to cover every edge at least once at every $\Delta$ consecutive time steps. In both cases we wish to minimize the total number of "vertex appearances" that are needed to cover the whole graph. We present a thorough investigation of the computational complexity and approximability of these two temporal covering problems. In particular, we provide strong hardness results, complemented by various approximation and exact algorithms. Some of our algorithms are polynomial-time, while others are asymptotically almost optimal under the Exponential Time Hypothesis (ETH) and other plausible complexity assumptions.

Includes members:
  Member "temporal matching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multistage graph problems on a global budget")
  Member "how fast can we reach a target vertex in stochastic temporal graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the computational complexity of finding temporal paths under waiting time constraints")
  Member "the temporal explorer who returns to the base":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the computational complexity of finding temporal paths under waiting time constraints")
  Member "sliding window temporal graph coloring":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "computing maximum matchings in temporal graphs")
  Member "on problems as hard as cnf sat":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "adapting the bron kerbosch algorithm for enumerating maximal cliques in temporal graphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "computing maximum matchings in temporal graphs")
  Member "computing maximal cliques in link streams":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "span core decomposition for temporal networks algorithms and applications")
  Member "temporal network optimization subject to connectivity constraints":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "distributed computation and reconfiguration in actively dynamic networks")

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.CC(Computational Complexity)