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: "motifs in temporal networks"
  Abstract: Networks are a fundamental tool for modeling complex systems in a variety of domains including social and communication networks as well as biology and neuroscience. The counts of small subgraph patterns in networks, called network motifs, are crucial to understanding the structure and function of these systems. However, the role of network motifs for temporal networks, which contain many timestamped links between nodes, is not well understood.   Here we develop a notion of a temporal network motif as an elementary unit of temporal networks and provide a general methodology for counting such motifs. We define temporal network motifs as induced subgraphs on sequences of edges, design several fast algorithms for counting temporal network motifs, and prove their runtime complexity. We also show that our fast algorithms achieve 1.3x to 56.5x speedups compared to a baseline method.   We use our algorithms to count temporal network motifs in a variety of real-world datasets. Results show that networks from different domains have significantly different motif frequencies, whereas networks from the same domain tend to have similar motif frequencies. We also find that measuring motif counts at various time scales reveals different behavior.

Connected through hyperedge HE-1 (induced by source paper "hypergraph motifs concepts algorithms and discoveries"):
  with members:
    - "how much and when do we need higher order information in hypergraphs a case study on hyperedge prediction"
    - "heterogeneous network motifs"
    - "edmot an edge enhancement approach for motif aware community detection"
    - "hypergraph clustering with categorical edge labels"
    - "motivo fast motif counting via succinct color coding and adaptive sampling"
    - "mining frequent patterns in evolving graphs"
    - "rept a streaming algorithm of approximating global and local triangle counts in parallel"
    - "simplicial closure and higher order link prediction"

Connected through hyperedge HE-2 (induced by source paper "finding temporal patterns using algebraic fingerprints"):
  with members:
    - "approximately counting and sampling small witnesses using a colourful decision oracle"
    - "the computational complexity of finding temporal paths under waiting time constraints"
    - "motivo fast motif counting via succinct color coding and adaptive sampling"
    - "mining frequent patterns in evolving graphs"
    - "a motif based approach for identifying controversy"
    - "stream graphs and link streams for the modeling of interactions over time"
    - "higher order organization of complex networks"
    - "on the complexity of rainbow coloring problems"

Connected through hyperedge HE-3 (induced by source paper "graph generators state of the art and open challenges"):
  with members:
    - "a survey on theoretical advances of community detection in networks"
    - "graphvae towards generation of small graphs using variational autoencoders"
    - "graphrnn generating realistic graphs with deep auto regressive models"
    - "learning deep generative models of graphs"
    - "gmark schema driven generation of graphs and queries"
    - "g core a core for future graph query languages"
    - "darwini generating realistic large scale social graphs"
    - "an introduction to temporal graphs an algorithmic perspective"

Connected through hyperedge HE-4 (induced by source paper "item independent temporal motifs to summarize and compare temporal networks"):
  with members:
    - "understanding information flow in cascades using network motifs"
    - "community interaction and conflict on the web"
    - "a sampling framework for counting temporal motifs"
    - "higher order organization of complex networks"
    - "an introduction to temporal graphs an algorithmic perspective"
    - "exploring the structure and function of temporal networks with dynamic graphlets"

Connected through hyperedge HE-5 (induced by source paper "detecting mixing services via mining bitcoin transaction network with hybrid motifs"):
  with members:
    - "anti money laundering in bitcoin experimenting with graph convolutional networks for financial forensics"
    - "identifying illicit accounts in large scale e payment networks a graph representation learning approach"
    - "mind your credit assessing the health of the ripple credit network"
    - "higher order organization of complex networks"
    - "traveling the silk road a measurement analysis of a large anonymous online marketplace"

Connected through hyperedge HE-6 (induced by source paper "novel edge and density metrics for link cohesion"):
  with members:
    - "trusses and trapezes easily interpreted communities in social networks"
    - "socrates a system for scalable graph analytics"
    - "a novel measure of edge centrality in social networks"

Connected through hyperedge HE-7 (induced by source paper "flow computation in temporal interaction networks"):
  with members:
    - "flow motifs in interaction networks"
    - "subgraph isomorphism in temporal networks"
    - "efficient subgraph matching on billion node graphs"

Connected through hyperedge HE-8 (induced by source paper "a hybrid approach to temporal pattern matching"):
  with members:
    - "mining maximal span cores from temporal 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)