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 "adaptive influence maximization in dynamic social networks"):
  Abstract: For the purpose of propagating information and ideas through a social network, a seeding strategy aims to find a small set of seed users that are able to maximize the spread of the influence, which is termed influence maximization problem. Despite a large number of works have studied this problem, the existing seeding strategies are limited to the models that cannot fully capture the characteristics of real-world social networks. In fact, due to high-speed data transmission and large population of participants, the diffusion processes in real-world social networks have many aspects of uncertainness. As shown in the experiments, when taking such uncertainness into account, the state-of-the-art seeding strategies are pessimistic as they fail to trace the influence diffusion. In this paper, we study the strategies that select seed users in an adaptive manner. We first formally model the dynamic independent Cascade model and introduce the concept of adaptive seeding strategy. Then, based on the proposed model, we show that a simple greedy adaptive seeding strategy finds an effective solution with a provable performance guarantee. Besides the greedy algorithm, an efficient heuristic algorithm is provided for better scalability. Extensive experiments have been performed on both the real-world networks and synthetic power-law networks. The results herein demonstrate the superiority of the adaptive seeding strategies to other baseline methods.

Includes members:
  Member "scalable methods for adaptively seeding a social network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "time constrained adaptive influence maximization")
  Member "minimizing seed set selection with probabilistic coverage guarantee in a social network":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficient approximation algorithms for adaptive seed minimization")
  Member "influence maximization in continuous time diffusion networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "black box submodular maximization discrete and continuous settings")
  Member "adaptive submodularity theory and applications in active learning and stochastic optimization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "comprehensive and efficient data labeling via adaptive model scheduling")

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)