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: "tight lower bounds on graph embedding problems"
  Abstract: We prove that unless the Exponential Time Hypothesis (ETH) fails, deciding if there is a homomorphism from graph $G$ to graph $H$ cannot be done in time $|V(H)|^{o(|V(G)|)}$. We also show an exponential-time reduction from Graph Homomorphism to Subgraph Isomorphism. This rules out (subject to ETH) a possibility of $|V(H)|^{o(|V(H)|)}$-time algorithm deciding if graph $G$ is a subgraph of $H$. For both problems our lower bounds asymptotically match the running time of brute-force algorithms trying all possible mappings of one graph into another. Thus, our work closes the gap in the known complexity of these fundamental problems. #R##N#Moreover, as a consequence of our reductions conditional lower bounds follow for other related problems such as Locally Injective Homomorphism, Graph Minors, Topological Graph Minors, Minimum Distortion Embedding and Quadratic Assignment Problem.

Connected through hyperedge HE-1 (induced by source paper "the fine grained complexity of computing the tutte polynomial of a linear matroid"):
  with members:
    - "fine grained dichotomies for the tutte plane and boolean csp"
    - "assigning channels via the meet in the middle approach"
    - "exponential time complexity of the permanent and the tutte polynomial"
    - "inapproximability of the tutte polynomial"
    - "computing the tutte polynomial in vertex exponential time"

Connected through hyperedge HE-2 (induced by source paper "hedonic seat arrangement problems"):
  with members:
    - "graphical one sided markets"
    - "computational complexity of hedonic games on sparse graphs"
    - "hedonic games with graph restricted communication"

Connected through hyperedge HE-3 (induced by source paper "subgraph isomorphism on graph classes that exclude a substructure"):
  with members:
    - "characterizing the easy to find subgraphs from the viewpoint of polynomial time algorithms kernels and turing kernels"
    - "on the computational complexity of vertex integrity and component order connectivity"
    - "everything you always wanted to know about the parameterized complexity of subgraph isomorphism but were afraid to ask"
    - "surface split decompositions and subgraph isomorphism in graphs on surfaces"
    - "planar subgraph isomorphism revisited"
    - "subgraph isomorphism in planar graphs and related problems"

Connected through hyperedge HE-4 (induced by source paper "fine grained complexity of graph homomorphism problem for bounded treewidth graphs"):
  with members:
    - "deleting vertices to graphs of bounded genus"
    - "problems parameterized by treewidth tractable in single exponential time a logical approach"
    - "known algorithms on graphs of bounded treewidth are probably optimal"

Connected through hyperedge HE-5 (induced by source paper "tight lower bounds for list edge coloring"):
  with members:
    - "known algorithms for edge clique cover are probably optimal"
    - "narrow sieves for parameterized paths and packings"

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)