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: "an introduction to temporal graphs an algorithmic perspective"
  Abstract: A \emph{temporal graph} is, informally speaking, a graph that changes with time. When time is discrete and only the relationships between the participating entities may change and not the entities themselves, a temporal graph may be viewed as a sequence $G_1,G_2\ldots,G_l$ of static graphs over the same (static) set of nodes $V$. Though static graphs have been extensively studied, for their temporal generalization we are still far from having a concrete set of structural and algorithmic principles. Recent research shows that many graph properties and problems become radically different and usually substantially more difficult when an extra time dimension in added to them. Moreover, there is already a rich and rapidly growing set of modern systems and applications that can be naturally modeled and studied via temporal graphs. This, further motivates the need for the development of a temporal extension of graph theory. We survey here recent results on temporal graphs and temporal graph problems that have appeared in the Computer Science community.

Connected through hyperedge HE-1 (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"
    - "motifs in temporal networks"
    - "g core a core for future graph query languages"
    - "darwini generating realistic large scale social graphs"

Connected through hyperedge HE-2 (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"
    - "motifs in temporal networks"
    - "higher order organization of complex networks"
    - "exploring the structure and function of temporal networks with dynamic graphlets"

Connected through hyperedge HE-3 (induced by source paper "edge disjoint branchings in temporal graphs"):
  with members:
    - "stream graphs and link streams for the modeling of interactions over time"
    - "time varying graphs and social network analysis temporal indicators and metrics"
    - "time varying graphs and dynamic networks"

Connected through hyperedge HE-4 (induced by source paper "multistage s t path confronting similarity with dissimilarity"):
  with members:
    - "the complexity of finding small separators in temporal graphs"

Connected through hyperedge HE-5 (induced by source paper "practice of streaming and dynamic graphs concepts models systems and parallelism"):
  with members:
    - "storing and querying large scale spatio temporal graphs with high throughput edge insertions"
    - "parallel batch dynamic graph connectivity"
    - "demystifying graph databases analysis and taxonomy of data organization system designs and graph queries"
    - "graph processing on fpgas taxonomy survey challenges"
    - "slim fly a cost effective low diameter network topology"
    - "red blue pebbling revisited near optimal parallel matrix matrix multiplication"
    - "dynamic algorithms for the massively parallel computation model"
    - "fatpaths routing in supercomputers data centers and clouds with low diameter networks when shortest paths fall short"

Connected through hyperedge HE-6 (induced by source paper "the computational complexity of finding temporal paths under waiting time constraints"):
  with members:
    - "an adaptive version of brandes algorithm for betweenness centrality"
    - "efficient computation of optimal temporal walks under waiting time constraints"
    - "how fast can we reach a target vertex in stochastic temporal graphs"
    - "temporal cliques admit sparse spanners"
    - "fixed parameter algorithms for maximum profit facility location under matroid constraints"
    - "the temporal explorer who returns to the base"
    - "changing times to minimise reachability in temporal graphs"
    - "deleting edges to restrict the size of an epidemic in temporal networks"

Connected through hyperedge HE-7 (induced by source paper "diffusion on dynamic contact networks with indirect transmission links"):
  with members:
    - "lightweight mobile ad hoc network routing protocols for smartphones"
    - "impact of indirect contacts in emerging infectious disease on social networks"
    - "least cost influence maximization across multiple social networks"
    - "diffusion in colocation contact networks the impact of nodal spatiotemporal dynamics"
    - "common neighbours and the local community paradigm for topological link prediction in bipartite networks"
    - "latent self exciting point process model for spatial temporal networks"
    - "time varying graphs and dynamic networks"
    - "information propagation speed in mobile and delay tolerant networks"

Connected through hyperedge HE-8 (induced by source paper "enumerating isolated cliques in temporal networks"):
  with members:
    - "community discovery in dynamic networks a survey"
    - "listing all maximal k plexes in temporal graphs"
    - "the parameterized complexity of finding secluded solutions to some classical optimization problems on graphs"
    - "enumerating maximal cliques in link streams with durations"
    - "stream graphs and link streams for the modeling of interactions over time"
    - "adapting the bron kerbosch algorithm for enumerating maximal cliques in temporal graphs"
    - "computing maximal cliques in link streams"
    - "parameterized complexity of secluded connectivity problems"

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.DM(Discrete Mathematics)