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: "complexity of the steiner network problem with respect to the number of terminals"
  Abstract: In the Directed Steiner Network problem we are given an arc-weighted digraph $G$, a set of terminals $T \subseteq V(G)$, and an (unweighted) directed request graph $R$ with $V(R)=T$. Our task is to output a subgraph $G' \subseteq G$ of the minimum cost such that there is a directed path from $s$ to $t$ in $G'$ for all $st \in A(R)$. #R##N#It is known that the problem can be solved in time $|V(G)|^{O(|A(R)|)}$ [Feldman&Ruhl, SIAM J. Comput. 2006] and cannot be solved in time $|V(G)|^{o(|A(R)|)}$ even if $G$ is planar, unless Exponential-Time Hypothesis (ETH) fails [Chitnis et al., SODA 2014]. However, as this reduction (and other reductions showing hardness of the problem) only shows that the problem cannot be solved in time $|V(G)|^{o(|T|)}$ unless ETH fails, there is a significant gap in the complexity with respect to $|T|$ in the exponent. #R##N#We show that Directed Steiner Network is solvable in time $f(R)\cdot |V(G)|^{O(c_g \cdot |T|)}$, where $c_g$ is a constant depending solely on the genus of $G$ and $f$ is a computable function. We complement this result by showing that there is no $f(R)\cdot |V(G)|^{o(|T|^2/ \log |T|)}$ algorithm for any function $f$ for the problem on general graphs, unless ETH fails.

Connected through hyperedge HE-1 (induced by source paper "tight bounds for planar strongly connected steiner subgraph with fixed number of terminals and extensions"):
  with members:
    - "fpt inapproximability of directed cut and connectivity problems"
    - "the parameterized complexity of finding point sets with hereditary properties"
    - "homomorphisms are a good basis for counting small subgraphs"
    - "parameterized approximation algorithms for directed steiner network problems"
    - "the graph motif problem parameterized by the structure of the input graph"
    - "on subexponential parameterized algorithms for steiner tree and directed subset tsp on planar graphs"
    - "on the parameterized complexity of red blue points separation"
    - "subexponential parameterized algorithms for planar and apex minor free graphs via low treewidth pattern covering"

Connected through hyperedge HE-2 (induced by source paper "parameterized approximation algorithms for directed steiner network problems"):
  with members:
    - "eth hardness of approximating 2 csps and directed steiner network"
    - "the complexity landscape of fixed parameter directed steiner network problems"
    - "from gap eth to fpt inapproximability clique dominating set and more"
    - "on subexponential parameterized algorithms for steiner tree and directed subset tsp on planar graphs"
    - "parameterized complexity and approximability of directed odd cycle transversal"
    - "subexponential parameterized algorithms for planar and apex minor free graphs via low treewidth pattern covering"
    - "almost polynomial ratio eth hardness of approximating densest k subgraph"
    - "fixed parameter approximations for k center problems in low highway dimension graphs"

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.DM(Discrete Mathematics)