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: "minimizing flow time in the wireless gathering problem"
  Abstract: We address the problem of efficient data gathering in a wireless network through multi-hop communication. We focus on the objective of minimizing the maximum flow time of a data packet. We prove that no polynomial time algorithm for this problem can have approximation ratio less than $\Omega(m^{1/3)$ when $m$ packets have to be transmitted, unless $P = NP$. We then use resource augmentation to assess the performance of a FIFO-like strategy. We prove that this strategy is 5-speed optimal, i.e., its cost remains within the optimal cost if we allow the algorithm to transmit data at a speed 5 times higher than that of the optimal solution we compare to.

Connected through hyperedge HE-1 (induced by source paper "maximum induced matching algorithms via vertex ordering characterizations"):
  with members:
    - "towards a unified view of linear structure on graph classes"
    - "a linear time algorithm for maximum cardinality matching on cocomparability graphs"
    - "linear time lexdfs on cocomparability graphs"
    - "ordering without forbidden patterns"
    - "a simple polynomial algorithm for the longest path problem on cocomparability graphs"

Connected through hyperedge HE-2 (induced by source paper "independent set induced matching and pricing connections and tight subexponential time approximation hardnesses"):
  with members:
    - "completely inapproximable monotone and antimonotone parameterized problems"
    - "on problems as hard as cnf sat"
    - "fixed parameter and approximation algorithms a new look"
    - "graph pricing problem on bounded treewidth bounded genus and k partite graphs"
    - "subexponential and fpt time inapproximability of independent set and related problems"
    - "graph products revisited tight approximation hardness of induced matching poset dimension and more"
    - "algorithmic pricing via virtual valuations"
    - "exponential time approximation of hard problems"

Connected through hyperedge HE-3 (induced by source paper "graph products revisited tight approximation hardness of induced matching poset dimension and more"):
  with members:
    - "stackelberg network pricing games"

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)