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: "sparse fault tolerant bfs trees"
  Abstract: This paper addresses the problem of designing a sparse {\em fault-tolerant} BFS tree, or {\em FT-BFS tree} for short, namely, a sparse subgraph $T$ of the given network $G$ such that subsequent to the failure of a single edge or vertex, the surviving part $T'$ of $T$ still contains a BFS spanning tree for (the surviving part of) $G$. Our main results are as follows. We present an algorithm that for every $n$-vertex graph $G$ and source node $s$ constructs a (single edge failure) FT-BFS tree rooted at $s$ with $O(n \cdot \min\{\Depth(s), \sqrt{n}\})$ edges, where $\Depth(s)$ is the depth of the BFS tree rooted at $s$. This result is complemented by a matching lower bound, showing that there exist $n$-vertex graphs with a source node $s$ for which any edge (or vertex) FT-BFS tree rooted at $s$ has $\Omega(n^{3/2})$ edges. We then consider {\em fault-tolerant multi-source BFS trees}, or {\em FT-MBFS trees} for short, aiming to provide (following a failure) a BFS tree rooted at each source $s\in S$ for some subset of sources $S\subseteq V$. Again, tight bounds are provided, showing that there exists a poly-time algorithm that for every $n$-vertex graph and source set $S \subseteq V$ of size $\sigma$ constructs a (single failure) FT-MBFS tree $T^*(S)$ from each source $s_i \in S$, with $O(\sqrt{\sigma} \cdot n^{3/2})$ edges, and on the other hand there exist $n$-vertex graphs with source sets $S \subseteq V$ of cardinality $\sigma$, on which any FT-MBFS tree from $S$ has $\Omega(\sqrt{\sigma}\cdot n^{3/2})$ edges. Finally, we propose an $O(\log n)$ approximation algorithm for constructing FT-BFS and FT-MBFS structures. The latter is complemented by a hardness result stating that there exists no $\Omega(\log n)$ approximation algorithm for these problems under standard complexity assumptions.

Connected through hyperedge HE-1 (induced by source paper "graph spanners a tutorial review"):
  with members:
    - "near additive spanners and near exact hopsets a unified view"
    - "some general structure for extremal sparsification problems"
    - "weighted additive spanners"
    - "near additive spanners in low polynomial deterministic congest time"
    - "multi level graph sketches via single level solvers"
    - "almost shortest paths and pram distance oracles in weighted graphs"
    - "an fpt algorithm for minimum additive spanner problem"
    - "distributed construction of light networks"

Connected through hyperedge HE-2 (induced by source paper "a trivial yet optimal solution to vertex fault tolerant spanners"):
  with members:
    - "preserving distances in very faulty graphs"
    - "optimal vertex fault tolerant spanners for fixed stretch"
    - "the greedy spanner is existentially optimal"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "compact and fast sensitivity oracles for single source distances"
    - "dual failure resilient bfs structure"
    - "the 4 3 additive spanner exponent is tight"
    - "fault tolerant approximate bfs structures"

Connected through hyperedge HE-3 (induced by source paper "generic single edge fault tolerant exact distance oracle"):
  with members:
    - "multiple source dual fault tolerant bfs trees"
    - "multiple edge fault tolerant approximate shortest path trees"
    - "dynamic dfs in undirected graphs breaking the o m barrier"
    - "compact and fast sensitivity oracles for single source distances"
    - "dual failure resilient bfs structure"
    - "faster replacement paths"
    - "approximate shortest paths avoiding a failed vertex optimal size data structures for unweighted graph"

Connected through hyperedge HE-4 (induced by source paper "preserving distances in very faulty graphs"):
  with members:
    - "connectivity oracles for graphs subject to vertex failures"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "linear size distance preservers"
    - "dual failure resilient bfs structure"
    - "better distance preservers and additive spanners"
    - "the 4 3 additive spanner exponent is tight"
    - "improved purely additive fault tolerant spanners"
    - "fault tolerant approximate shortest path trees"

Connected through hyperedge HE-5 (induced by source paper "optimal vertex fault tolerant spanners for fixed stretch"):
  with members:
    - "preserving distances in very faulty graphs"
    - "connectivity oracles for graphs subject to vertex failures"
    - "multiple edge fault tolerant approximate shortest path trees"
    - "improved distance sensitivity oracles via tree partitioning"
    - "compact and fast sensitivity oracles for single source distances"
    - "dual failure resilient bfs structure"
    - "improved purely additive fault tolerant spanners"
    - "fault tolerant approximate shortest path trees"

Connected through hyperedge HE-6 (induced by source paper "near optimal sized weight tolerant subgraph for single source shortest path"):
  with members:
    - "multiple edge fault tolerant approximate shortest path trees"
    - "an efficient strongly connected components algorithm in the fault tolerant model"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "dual failure resilient bfs structure"
    - "the 4 3 additive spanner exponent is tight"
    - "improved purely additive fault tolerant spanners"
    - "fault tolerant approximate shortest path trees"
    - "fault tolerant approximate bfs structures"

Connected through hyperedge HE-7 (induced by source paper "reachability preservers new extremal bounds and approximation algorithms"):
  with members:
    - "steiner point removal with distortion o log k"
    - "steiner point removal distant terminals don t really bother"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "linear size distance preservers"
    - "graph minors for preserving terminal distances approximately lower and upper bounds"
    - "dual failure resilient bfs structure"
    - "the 4 3 additive spanner exponent is tight"
    - "bypassing erd h o s girth conjecture hybrid stretch and sourcewise spanners"

Connected through hyperedge HE-8 (induced by source paper "multiple source dual fault tolerant bfs trees"):
  with members:
    - "multiple edge fault tolerant approximate shortest path trees"
    - "dynamic dfs in undirected graphs breaking the o m barrier"
    - "dual failure resilient bfs structure"
    - "improved purely additive fault tolerant spanners"
    - "fault tolerant approximate bfs structures"
    - "vertex fault tolerant additive spanners"
    - "fault tolerant spanners better and simpler"

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)