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: "spreading processes in multilayer networks"
  Abstract: Several systems can be modeled as sets of interconnected networks or networks with multiple types of connections, here generally called multilayer networks. Spreading processes such as information propagation among users of online social networks, or the diffusion of pathogens among individuals through their contact network, are fundamental phenomena occurring in these networks. However, while information diffusion in single networks has received considerable attention from various disciplines for over a decade, spreading processes in multilayer networks is still a young research area presenting many challenging research issues. In this paper, we review the main models, results and applications of multilayer spreading processes and discuss some promising research directions.

Connected through hyperedge HE-1 (induced by source paper "deep learning approach on information diffusion in heterogeneous networks"):
  with members:
    - "coupled deep learning for heterogeneous face recognition"
    - "meta path guided embedding for similarity search in large scale heterogeneous information networks"
    - "node2vec scalable feature learning for networks"
    - "deepcas an end to end predictor of information cascades"
    - "information diffusion in social networks in two phases"
    - "revisiting semi supervised learning with graph embeddings"
    - "a survey of heterogeneous information network analysis"
    - "line large scale information network embedding"

Connected through hyperedge HE-2 (induced by source paper "interacting spreading processes in multilayer networks"):
  with members:
    - "quantifying layer similarity in multiplex networks a systematic study"
    - "an effective rumor containing strategy"
    - "co diffusion of social contagions"
    - "seed selection for information cascade in multilayer networks"
    - "a multilayer network dataset of interaction and influence spreading in a virtual world"
    - "a picture is worth a thousand words an empirical study on the influence of content visibility on diffusion processes within a virtual world"
    - "competing spreading processes and immunization in multiplex networks"

Connected through hyperedge HE-3 (induced by source paper "link persistence and conditional distances in multiplex networks"):
  with members:
    - "a dynamic network model with persistent links and node specific latent variables with an application to the interbank market"
    - "an experimental investigation of hyperbolic routing with a smart forwarding plane in ndn"
    - "network mapping by replaying hyperbolic growth"
    - "on the diameter of hyperbolic random graphs"
    - "network geometry inference using common neighbors"
    - "sustaining the internet with hyperbolic mapping"

Connected through hyperedge HE-4 (induced by source paper "link prediction in multiplex networks based on interlayer similarity"):
  with members:
    - "qanet tensor decomposition approach for query based anomaly detection in heterogeneous information networks"
    - "a multilayer approach to multiplexity and link prediction in online geo social networks"
    - "a probabilistic model to resolve diversity accuracy challenge of recommendation systems"
    - "multiple routes transmitted epidemics on multiplex networks"
    - "diffusion of innovations over multiplex social networks"
    - "combinatorial analysis of multiple networks"

Connected through hyperedge HE-5 (induced by source paper "foundations of temporal text networks"):
  with members:
    - "detecting socio economic impact of cultural investment through geo social network analysis"
    - "graph embedding techniques applications and performance a survey"
    - "motifs in temporal networks"
    - "automated analysis of topic actor networks on twitter new approach to the analysis of socio semantic networks"
    - "when is a network a network multi order graphical model selection in pathways and temporal networks"
    - "modelling sequences and temporal networks with dynamic community structures"
    - "do cascades recur"
    - "clustering attributed graphs models measures and methods"

Connected through hyperedge HE-6 (induced by source paper "qanet tensor decomposition approach for query based anomaly detection in heterogeneous information networks"):
  with members:
    - "netspam a network based spam detection framework for reviews in online social media"
    - "a survey of heterogeneous information network analysis"
    - "graph based anomaly detection and description a survey"

Connected through hyperedge HE-7 (induced by source paper "quantifying layer similarity in multiplex networks a systematic study"):
  with members:
    - "abacus frequent pattern mining based community discovery in multidimensional networks"

Connected through hyperedge HE-8 (induced by source paper "seed selection for information cascade in multilayer networks"):
  with members:
    - "do we really need to catch them all a new user guided social media crawling method"
    - "finding influential users in social media using association rule learning"
    - "identifying a set of influential spreaders in complex networks"

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)