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 approximation algorithms for k connected m dominating set problems"):
  Abstract: A graph is $k$-connected if it has $k$ internally-disjoint paths between every pair of nodes. A subset $S$ of nodes in a graph $G$ is a $k$-connected set if the subgraph $G[S]$ induced by $S$ is $k$-connected; $S$ is an $m$-dominating set if every $v \in V \setminus S$ has at least $m$ neighbors in $S$. If $S$ is both $k$-connected and $m$-dominating then $S$ is a $k$-connected $m$-dominating set, or $(k,m)$-cds for short. In the $k$-Connected $m$-Dominating Set ($(k,m)$-CDS) problem the goal is to find a minimum weight $(k,m)$-cds in a node-weighted graph. We consider the case $m \geq k$ and obtain the following approximation ratios. For unit disc-graphs we obtain ratio $O(k\ln k)$, improving the previous ratio $O(k^2 \ln k)$. For general graphs we obtain the first non-trivial approximation ratio $O(k^2 \ln n)$.

Includes members:
  Member "approximation algorithm for minimum weight fault tolerant virtual backbone in unit disk graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "2 node connectivity network design")
  Member "constant approximation algorithms for highly connected multi dominating sets in unit disk graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "approximation algorithm for minimum weight connected m fold dominating set")
  Member "spider covers for prize collecting network activation problem":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "node weighted network design in planar and minor closed families of graphs")
  Member "parameters of two prover one round game and the hardness of connectivity problems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "network design for s t effective resistance")
  Member "an improved approximation algorithm for the minimum cost subset k connected subgraph problem":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "polylogarithmic approximation algorithm for k connected directed steiner tree on quasi bipartite graphs")
  Member "approximating subset k connectivity problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "polylogarithmic approximation algorithm for k connected directed steiner tree on quasi bipartite graphs")

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)