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: "coloring k colorable graphs using relatively small palettes"
  Abstract: We obtain the following new coloring results: #R##N#* A 3-colorable graph on $n$ vertices with maximum degree~$\Delta$ can be colored, in polynomial time, using $O((\Delta \log\Delta)^{1/3} \cdot\log{n})$ colors. This slightly improves an $O((\Delta^{{1}/{3}} \log^{1/2}\Delta)\cdot\log{n})$ bound given by Karger, Motwani and Sudan. More generally, $k$-colorable graphs with maximum degree $\Delta$ can be colored, in polynomial time, using $O((\Delta^{1-{2}/{k}}\log^{1/k}\Delta) \cdot\log{n})$ colors. #R##N#* A 4-colorable graph on $n$ vertices can be colored, in polynomial time, using $\Ot(n^{7/19})$ colors. This improves an $\Ot(n^{2/5})$ bound given again by Karger, Motwani and Sudan. More generally, $k$-colorable graphs on $n$ vertices can be colored, in polynomial time, using $\Ot(n^{\alpha_k})$ colors, where $\alpha_5=97/207$, $\alpha_6=43/79$, $\alpha_7=1391/2315$, $\alpha_8=175/271$, ... #R##N#The first result is obtained by a slightly more refined probabilistic analysis of the semidefinite programming based coloring algorithm of Karger, Motwani and Sudan. The second result is obtained by combining the coloring algorithm of Karger, Motwani and Sudan, the combinatorial coloring algorithms of Blum and an extension of a technique of Alon and Kahale (which is based on the Karger, Motwani and Sudan algorithm) for finding relatively large independent sets in graphs that are guaranteed to have very large independent sets. The extension of the Alon and Kahale result may be of independent interest.

Connected through hyperedge HE-1 (induced by source paper "approximating the orthogonality dimension of graphs and hypergraphs"):
  with members:
    - "on a fractional version of haemers bound"
    - "algebraic approach to promise constraint satisfaction"
    - "linear index coding via semidefinite programming"
    - "conditional hardness for approximate coloring"
    - "approximate graph coloring by semidefinite programming"

Connected through hyperedge HE-2 (induced by source paper "wireless capacity with arbitrary gain matrix"):
  with members:
    - "approximation algorithms for wireless link scheduling with flexible data rates"
    - "nearly optimal bounds for distributed wireless scheduling in the sinr model"
    - "the topology of wireless communication"
    - "wireless capacity with oblivious power in general metrics"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"
    - "approximation algorithms for secondary spectrum auctions"
    - "approximate graph coloring by semidefinite programming"

Connected through hyperedge HE-3 (induced by source paper "linear index coding via semidefinite programming"):
  with members:
    - "broadcasting with side information"
    - "on the relation between the index coding and the network coding problems"
    - "conditional hardness for approximate coloring"
    - "approximate graph coloring by semidefinite programming"

Connected through hyperedge HE-4 (induced by source paper "conditional hardness for approximate coloring"):
  with members:
    - "approximate graph coloring by semidefinite programming"

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)