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: "non altering time scales for aggregation of dynamic networks into series of graphs"
  Abstract: Many dynamic networks coming from real-world contexts are link streams, i.e. a finite collection of triplets $(u,v,t)$ where $u$ and $v$ are two nodes having a link between them at time $t$. A very large number of studies on these objects start by aggregating the data in disjoint time windows of length $\Delta$ in order to obtain a series of graphs on which are made all subsequent analyses. Here we are concerned with the impact of the chosen $\Delta$ on the obtained graph series. We address the fundamental question of knowing whether a series of graphs formed using a given $\Delta$ faithfully describes the original link stream. We answer the question by showing that such dynamic networks exhibit a threshold for $\Delta$, which we call the \emph{saturation scale}, beyond which the properties of propagation of the link stream are altered, while they are mostly preserved before. We design an automatic method to determine the saturation scale of any link stream, which we apply and validate on several real-world datasets.

Connected through hyperedge HE-1 (induced by source paper "degree based outlier detection within ip traffic modelled as a link stream"):
  with members:
    - "stream graphs and link streams for the modeling of interactions over time"
    - "discovering patterns of interest in ip traffic using cliques in bipartite link streams"
    - "an algebraic approach to temporal network analysis based on temporal quantities"
    - "a unifying model for representing time varying graphs"
    - "network traffic anomaly detection"
    - "graph based anomaly detection and description a survey"
    - "temporal reachability graphs"
    - "netsimile a scalable approach to size independent network similarity"

Connected through hyperedge HE-2 (induced by source paper "stream graphs and link streams for the modeling of interactions over time"):
  with members:
    - "degree based outlier detection within ip traffic modelled as a link stream"
    - "movie rating prediction using content based and link stream features"
    - "motifs in temporal networks"
    - "discovering patterns of interest in ip traffic using cliques in bipartite link streams"
    - "time series analysis of temporal networks"
    - "graphprints towards a graph analytic method for network anomaly detection"
    - "semirings for temporal network analysis"
    - "on multiaspect graphs"

Connected through hyperedge HE-3 (induced by source paper "discovering patterns of interest in ip traffic using cliques in bipartite link streams"):
  with members:
    - "stream graphs and link streams for the modeling of interactions over time"
    - "enumerating maximal cliques in temporal graphs"
    - "computing maximal cliques in link streams"
    - "a unifying model for representing time varying graphs"

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)