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: "real time influence maximization on dynamic social streams"
  Abstract: Influence maximization (IM), which selects a set of k users (called seeds) to maximize the influence spread over a social network, is a fundamental problem in a wide range of applications such as viral marketing and network monitoring. Existing IM solutions fail to consider the highly dynamic nature of social influence, which results in either poor seed qualities or long processing time when the network evolves. To address this problem, we define a novel IM query named Stream Influence Maximization (SIM) on social streams. Technically, SIM adopts the sliding window model and maintains a set of k seeds with the largest influence value over the most recent social actions. Next, we propose the Influential Checkpoints (IC) framework to facilitate continuous SIM query processing. The IC framework creates a checkpoint for each window shift and ensures an e-approximate solution. To improve its efficiency, we further devise a Sparse Influential Checkpoints (SIC) framework which selectively keeps O(logN/β checkpoints for a sliding window of size N and maintains an e(1−β)/2-approximate solution. Experimental results on both real-world and synthetic datasets confirm the effectiveness and efficiency of our proposed frameworks against the state-of-the-art IM approaches.

Connected through hyperedge HE-1 (induced by source paper "locec local community based edge classification in large online social networks"):
  with members:
    - "a comprehensive survey on graph neural networks"
    - "model slicing for supporting complex analytics with elastic inference cost and resource constraints"
    - "revenue maximization in incentivized social advertising"
    - "xgboost a scalable tree boosting system"
    - "database meets deep learning challenges and opportunities"
    - "fast r cnn"
    - "romantic partnerships and the dispersion of social ties a network analysis of relationship status on facebook"
    - "social influence in social advertising evidence from field experiments"

Connected through hyperedge HE-2 (induced by source paper "coresets for minimum enclosing balls over sliding windows"):
  with members:
    - "efficient representative subset selection over sliding windows"
    - "near optimal coresets of kernel density estimates"
    - "coresets for kernel regression"
    - "submodular optimization over sliding windows"
    - "streamed learning one pass svms"

Connected through hyperedge HE-3 (induced by source paper "efficient representative subset selection over sliding windows"):
  with members:
    - "submodular optimization over sliding windows"
    - "adaptive maximization of pointwise submodular functions with budget constraint"

Connected through hyperedge HE-4 (induced by source paper "tracking influential nodes in time decaying dynamic interaction networks"):
  with members:
    - "tracking influential individuals in dynamic networks"
    - "submodular optimization over sliding windows"
    - "robust influence maximization"
    - "boosting information spread an algorithmic approach"
    - "submodular maximization over sliding windows"
    - "online influence maximization"
    - "influence maximization near optimal time complexity meets practical efficiency"
    - "the bursty dynamics of the twitter information network"

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.SI(Social and Information Networks)