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 "near optimal fully dynamic densest subgraph"):
  Abstract: We give the first fully dynamic algorithm which maintains a $(1+\epsilon)$-approximate densest subgraph in worst-case time $\text{poly}(\log n, \epsilon^{-1})$ per update with high probability. Dense subgraph discovery is an important primitive for many real-world applications such as community detection, link spam detection, distance query indexing, and computational biology. Our result improves upon the previous best approximation factor of $(4+\epsilon)$ for fully dynamic densest subgraph obtained by [Bhattacharya-Henzinger-Nanongkai-Tsourakakis, STOC`15]. Our algorithm combines the uniform sparsification technique used in [Mitzenmacher-Pachocki-Peng-Tsourakakis-Xu, KDD`15] and [McGregor-Tench-Vorotnikova-Vu, MFCS`15] along with an augmenting path-like dual adjustment technique to maintain an approximate solution efficiently.

Includes members:
  Member "distributed dense subgraph detection and low outdegree orientation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed approximation algorithms for maximum matching in graphs and hypergraphs")
  Member "new algorithms and lower bounds for all pairs max flow in undirected graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on two measures of distance between fully labelled trees")
  Member "inapproximability of maximum biclique problems minimum k cut and densest at least k subgraph from the small set expansion hypothesis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "principal fairness removing bias via projections")
  Member "fully dynamic approximate maximum matching and minimum vertex cover in o log 3 n worst case update time":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "egalitarian graph orientations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "balanced schnyder woods for planar triangulations an experimental study with applications to graph drawing and graph separators")
  Member "the ubiquity of large graphs and surprising challenges of graph processing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "demystifying graph databases analysis and taxonomy of data organization system designs and graph queries")
  Member "new deterministic approximation algorithms for fully dynamic matching":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "popular conjectures as a barrier for dynamic planar graph algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "rounding dynamic matchings against an adaptive adversary")

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)