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: "biconnectivity st numbering and other applications of dfs using o n bits"
  Abstract: We consider space efficient implementations of some classical applications of DFS including the problem of testing biconnectivity and $2$-edge connectivity, finding cut vertices and cut edges, computing chain decomposition and $st$-numbering of a given undirected graph $G$ on $n$ vertices and $m$ edges. Classical algorithms for them typically use DFS and some $\Omega (\lg n)$ bits\footnote{We use $\lg$ to denote logarithm to the base $2$.} of information at each vertex. Building on a recent $O(n)$-bits implementation of DFS due to Elmasry et al. (STACS 2015) we provide $O(n)$-bit implementations for all these applications of DFS. Our algorithms take $O(m \lg^c n \lg\lg n)$ time for some small constant $c$ (where $c \leq 2$). Central to our implementation is a succinct representation of the DFS tree and a space efficient partitioning of the DFS tree into connected subtrees, which maybe of independent interest for designing other space efficient graph algorithms.

Connected through hyperedge HE-1 (induced by source paper "indexing graph search trees and applications"):
  with members:
    - "succinct data structures for families of interval graphs"
    - "improved space efficient linear time algorithms for some classical graph problems"
    - "space efficient biconnected components and recognition of outerplanar graphs"
    - "fast and compact planar embeddings"
    - "succinct representations of permutations and functions"

Connected through hyperedge HE-2 (induced by source paper "space efficient algorithms for breadth depth search"):
  with members:
    - "improved time space trade offs for computing voronoi diagrams"
    - "space efficient algorithms for longest increasing subsequence"
    - "improved space efficient linear time algorithms for some classical graph problems"

Connected through hyperedge HE-3 (induced by source paper "optimal in place algorithms for basic graph problems"):
  with members:
    - "canonizing graphs of bounded tree width in logspace"
    - "a simple test on 2 vertex and 2 edge connectivity"
    - "space time trade offs for stack based algorithms"

Connected through hyperedge HE-4 (induced by source paper "frameworks for designing in place graph algorithms"):
  with members:
    - "succinct choice dictionaries"
    - "canonizing graphs of bounded tree width in logspace"
    - "exact algorithms via monotone local search"
    - "selection from read only memory with limited workspace"
    - "the isomorphism problem for planar 3 connected graphs is in unambiguous logspace"
    - "radix sorting with no extra space"

Connected through hyperedge HE-5 (induced by source paper "improved space efficient linear time algorithms for some classical graph problems"):
  with members:
    - "a simple test on 2 vertex and 2 edge connectivity"
    - "the wavelet trie maintaining an indexed sequence of strings in compressed space"

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)