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 "improved algorithms for maintaining dfs tree in undirected graphs"):
  Abstract: Depth first search (DFS) tree is one of the most well-known data structures for designing efficient graph algorithms. Given an undirected graph $G=(V,E)$ with $n$ vertices and $m$ edges, the textbook algorithm takes $O(n+m)$ time to construct a DFS tree. In this paper, we study the problem of maintaining a DFS tree when the graph is undergoing updates. Formally, we show the following results. #R##N#Incremental DFS tree: Given any arbitrary online sequence of edge or vertex insertions, we can report a DFS tree in $O(n)$ worst case time per operation, and $O\left(\min\{m \log n + n \log^2 n, n^2\}\right)$ preprocessing time. #R##N#Fault tolerant DFS tree: There exists a data structure of size $O(m \log n)$, such that given any set $\mathcal{F}$ of failed vertices or edges, it can report a DFS tree of the graph $G \setminus \mathcal{F}$ in $O(n|\mathcal{F}|\log^2 n)$ time. #R##N#Fully dynamic DFS tree: Given any arbitrary online sequence of edge or vertex updates, we can report a DFS tree in $O(\sqrt{nm}\log^{1.5} n)$ worst case time per operation. #R##N#Our result for incremental DFS tree improves the previous $O(n \log^3 n)$ worst case update time by Baswana et al., and matches the trivial $\Omega(n)$ lower bound when it is required to explicitly output the DFS tree. Our other results also improve the corresponding state-of-the-art results by Baswana et al. as well. Our work builds on the framework of the breakthrough work by Baswana et al., together with a novel use of a tree-partition lemma by Duan and Zhang, and the celebrated fractional cascading technique by Chazelle and Guibas.

Includes members:
  Member "dynamic dfs in undirected graphs breaking the o m barrier":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "depth first search in the semi streaming model")
  Member "improved distance sensitivity oracles via tree partitioning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "approximate distance oracles subject to multiple vertex failures")
  Member "simple deterministic algorithms for fully dynamic maximal matching":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dynamic graph algorithms with batch updates in the massively parallel computation model")
  Member "sorted range reporting":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "four dimensional dominance range reporting in linear space")
  Member "fully dynamic maximal matching in o log n update time":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "coarse grained complexity for dynamic algorithms")

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)