human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "discovering patterns of interest in ip traffic using cliques in bipartite link streams"):
  Abstract: Studying IP traffic is crucial for many applications. We focus here on the detection of (structurally and temporally) dense sequences of interactions, that may indicate botnets or coordinated network scans. More precisely, we model a MAWI capture of IP traffic as a link streams, i.e. a sequence of interactions $(t_1 , t_2 , u, v)$ meaning that devices $u$ and $v$ exchanged packets from time $t_1$ to time $t_2$ . This traffic is captured on a single router and so has a bipartite structure: links occur only between nodes in two disjoint sets. We design a method for finding interesting bipartite cliques in such link streams, i.e. two sets of nodes and a time interval such that all nodes in the first set are linked to all nodes in the second set throughout the time interval. We then explore the bipartite cliques present in the considered trace. Comparison with the MAWILab classification of anomalous IP addresses shows that the found cliques succeed in detecting anomalous network activity.

Includes members:
  Member "non altering time scales for aggregation of dynamic networks into series of graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "degree based outlier detection within ip traffic modelled as a link stream")
  Member "stream graphs and link streams for the modeling of interactions over time":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "finding temporal patterns using algebraic fingerprints")
  Member "enumerating maximal cliques in temporal graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "span core decomposition for temporal networks algorithms and applications")
  Member "computing maximal cliques in link streams":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "span core decomposition for temporal networks algorithms and applications")
  Member "a unifying model for representing time varying graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "algorithmic networks central time to trigger expected emergent open endedness")

Question: Please tell me which class the source paper 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.DS(Data Structures and Algorithms)