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: "nestpp modeling thread dynamics in online discussion forums"
  Abstract: Online discussion forum creates an asynchronous conversation environment for online users to exchange ideas and share opinions through a unique thread-reply communication mode. Accurately modeling information dynamics under such a mode is important, as it provides a means of mining latent spread patterns and understanding user behaviors. In this paper, we design a novel temporal point process model to characterize information cascades in online discussion forums. The proposed model views the entire event space as a nested structure composed of main thread streams and their linked reply streams, and it explicitly models the correlations between these two types of streams through their intensity functions. Leveraging the Reddit data, we examine the performance of the designed model in different applications and compare it with other popular methods. The experimental results have shown that our model can produce competitive results, and it outperforms state-of-the-art methods in most cases.

Connected through hyperedge HE-1 (induced by source paper "socialgrid a tcn enhanced method for online discussion forecasting"):
  with members:
    - "modelling structure and predicting dynamics of discussion threads in online boards"
    - "personalized thread recommendation for mooc discussion forums"
    - "an empirical evaluation of generic convolutional and recurrent networks for sequence modeling"
    - "time series classification from scratch with deep neural networks a strong baseline"
    - "multi scale convolutional neural networks for time series classification"
    - "tideh time dependent hawkes process for predicting retweet dynamics"
    - "wavenet a generative model for raw audio"
    - "a convolutional encoder model for neural machine translation"

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)