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 "tight bounds for planar strongly connected steiner subgraph with fixed number of terminals and extensions"):
  Abstract: (see paper for full abstract) #R##N#Given a vertex-weighted directed graph $G=(V,E)$ and a set $T=\{t_1, t_2, \ldots t_k\}$ of $k$ terminals, the objective of the SCSS problem is to find a vertex set $H\subseteq V$ of minimum weight such that $G[H]$ contains a $t_{i}\rightarrow t_j$ path for each $i\neq j$. The problem is NP-hard, but Feldman and Ruhl [FOCS '99; SICOMP '06] gave a novel $n^{O(k)}$ algorithm for the SCSS problem, where $n$ is the number of vertices in the graph and $k$ is the number of terminals. We explore how much easier the problem becomes on planar directed graphs: #R##N#- Our main algorithmic result is a $2^{O(k)}\cdot n^{O(\sqrt{k})}$ algorithm for planar SCSS, which is an improvement of a factor of $O(\sqrt{k})$ in the exponent over the algorithm of Feldman and Ruhl. #R##N#- Our main hardness result is a matching lower bound for our algorithm: we show that planar SCSS does not have an $f(k)\cdot n^{o(\sqrt{k})}$ algorithm for any computable function $f$, unless the Exponential Time Hypothesis (ETH) fails. #R##N#The following additional results put our upper and lower bounds in context: #R##N#- In general graphs, we cannot hope for such a dramatic improvement over the $n^{O(k)}$ algorithm of Feldman and Ruhl: assuming ETH, SCSS in general graphs does not have an $f(k)\cdot n^{o(k/\log k)}$ algorithm for any computable function $f$. #R##N#- Feldman and Ruhl generalized their $n^{O(k)}$ algorithm to the more general Directed Steiner Network (DSN) problem; here the task is to find a subgraph of minimum weight such that for every source $s_i$ there is a path to the corresponding terminal $t_i$. We show that, assuming ETH, there is no $f(k)\cdot n^{o(k)}$ time algorithm for DSN on acyclic planar graphs.

Includes members:
  Member "fpt inapproximability of directed cut and connectivity problems":
    also connected through other hyperedges:
      (none)
  Member "complexity of the steiner network problem with respect to the number of terminals":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "parameterized approximation algorithms for directed steiner network problems")
  Member "the parameterized complexity of finding point sets with hereditary properties":
    also connected through other hyperedges:
      (none)
  Member "homomorphisms are a good basis for counting small subgraphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "local wl invariance and hidden shades of regularity")
  Member "parameterized approximation algorithms for directed steiner network problems":
    also connected through other hyperedges:
      (none)
  Member "the graph motif problem parameterized by the structure of the input graph":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "balanced connected subgraph problem in geometric intersection graphs")
  Member "on subexponential parameterized algorithms for steiner tree and directed subset tsp on planar graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "almost tight lower bounds for hard cutting problems in embedded graphs")
  Member "on the parameterized complexity of red blue points separation":
    also connected through other hyperedges:
      (none)

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)