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: "on strongly connected digraphs with bounded cycle length"
  Abstract: Abstract   Given a directed graph  G  = ( V ,  E ), a natural problem is to choose a minimum number of the edges in  E  such that, for any two vertices  u  and  v , if there is a path from  u  to  v  in  E , then there is a path from  u  to  v  among the chosen edges. We show that in graphs having no directed cycle with more than three edges, this problem is equivalent to Maximum Bipartite Matching. This leads to a small improvement in the performance guarantee of the previous best approximation algorithm for the general problem.

Connected through hyperedge HE-1 (induced by source paper "correspondent banking networks theory and experiment"):
  with members:
    - "towards unbiased bfs sampling"
    - "approximating the minimum equivalent digraph"

Connected through hyperedge HE-2 (induced by source paper "approximating minimum representations of key horn functions"):
  with members:
    - "hydras directed hypergraphs and horn formulas"
    - "hardness results for approximate pure horn cnf formulae minimization"

Connected through hyperedge HE-3 (induced by source paper "dual based approximation algorithms for cut based network connectivity problems"):
  with members:
    - "dual power assignment via second hamiltonian cycle"
    - "on min power steiner tree"
    - "a rounding by sampling approach to the minimum size k arc connected subgraph problem"
    - "approximating the minimum equivalent digraph"

Connected through hyperedge HE-4 (induced by source paper "dual fitting approximation algorithms for network connectivity problems"):
  with members:
    - "dual power assignment via second hamiltonian cycle"
    - "on min power steiner tree"
    - "approximating the minimum equivalent digraph"

Connected through hyperedge HE-5 (induced by source paper "dual power assignment via second hamiltonian cycle"):
  with members:
    - "approximating the minimum equivalent digraph"

Connected through hyperedge HE-6 (induced by source paper "algorithmic perspectives of network transitive reduction problems and their applications to synthesis and analysis of biological networks"):
  with members:
    - "exploring networks with traceroute like probes theory and simulations"
    - "approximating the minimum equivalent digraph"

Connected through hyperedge HE-7 (induced by source paper "a rounding by sampling approach to the minimum size k arc connected subgraph problem"):
  with members:
    - "improving christofides algorithm for the s t path tsp"
    - "online stochastic matching online actions based on offline statistics"
    - "approximating the minimum equivalent digraph"

Connected through hyperedge HE-8 (induced by source paper "approximating transitivity in directed networks"):
  with members:
    - "approximating the minimum equivalent digraph"

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)