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 "timed influence computation and maximization"):
  Abstract: We consider a cost model for diffusion in a network that captures both the scope of infection and its propagation time: The edges of the network have associated lengths which model transmission times, and influence scores are higher for faster propagation. We propose an intuitive measure of timed influence, which extends and unifies several classic measures, including the well-studied “binary” influence [Richardson and Domingos 2002; Kempe et al. 2003] (which only measures scope), a recently-studied threshold model of timed influence [Gomez-Rodriguez et al. 2011] (which considers a node influenced only within a fixed time horizon), and closeness centrality (which is extended from being defined for a single node to multiple seed nodes and from a fixed network to distributions). Finally, we provide the first highly scalable algorithms for timed influence computation and maximization. In particular, we improve by orders of magnitude the scalability of state-of-the-art threshold timed influence computation. Moreover, our design provides robust guarantees and is novel also as a theoretical contribution.

Includes members:
  Member "influence maximization near optimal time complexity meets practical efficiency":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "time constrained adaptive influence maximization")
  Member "sketch based influence maximization and computation scaling up with guarantees":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "rcelf a residual based approach for influence maximization problem")
  Member "all distances sketches revisited hip estimators for massive graphs analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sampling sketches for concave sublinear functions of frequencies")
  Member "axioms for centrality":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "maximizing influence based group shapley centrality")
  Member "in core computation of geometric centralities with hyperball a hundred billion nodes and beyond":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "computing top k closeness centrality faster in unweighted graphs")
  Member "trace complexity of network inference":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning mixtures of graphs from epidemic cascades")
  Member "scalable influence estimation in continuous time diffusion networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "approximate k cover in hypergraphs efficient algorithms and applications")
  Member "maximizing social influence in nearly optimal time":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "time constrained adaptive influence maximization")

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.SI(Social and Information Networks)