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: "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.

Connected through hyperedge HE-1 (induced by source paper "fault tolerant and fully dynamic dfs in undirected graphs simple yet efficient"):
  with members:
    - "incremental dfs algorithms a theoretical and experimental study"
    - "dynamic minimum spanning forest with subpolynomial worst case update time"
    - "fully dynamic maximal matching in constant update time"
    - "dynamic dfs in undirected graphs breaking the o m barrier"
    - "an improved algorithm for incremental dfs tree in undirected graphs"
    - "deterministic fully dynamic data structures for vertex cover and matching"
    - "dynamic connectivity connecting to networks and geometry"

Connected through hyperedge HE-2 (induced by source paper "connectivity oracles for graphs subject to vertex failures"):
  with members:
    - "dynamic minimum spanning forest with subpolynomial worst case update time"
    - "fully dynamic connectivity in o log n log log n 2 amortized expected time"
    - "faster randomized worst case update time for dynamic subgraph connectivity"
    - "dynamic dfs in undirected graphs breaking the o m barrier"
    - "incremental and fully dynamic subgraph connectivity for emergency planning"
    - "faster online matrix vector multiplication"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "improved bounds for 3sum k sum and linear degeneracy"

Connected through hyperedge HE-3 (induced by source paper "faster randomized worst case update time for dynamic subgraph connectivity"):
  with members:
    - "fully dynamic connectivity in o log n log log n 2 amortized expected time"
    - "dynamic dfs in undirected graphs breaking the o m barrier"
    - "fully dynamic minimum spanning forest with improved worst case update time"
    - "faster worst case update time for dynamic subgraph connectivity"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "dynamic graph connectivity with improved worst case update time and sublinear space"
    - "an improved randomized data structure for dynamic graph connectivity"
    - "faster worst case deterministic dynamic connectivity"

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.DS(Data Structures and Algorithms)