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: "a bit parallel russian dolls search for a maximum cardinality clique in a graph"
  Abstract: Finding the clique of maximum cardinality in an arbitrary graph is an NP-Hard problem that has many applications, which has motivated several approaches to solve it exactly despite its difficulty. In this paper, we propose an exact algorithm for the maximum clique problem based on the Russian Dolls Search method. In comparison to a first implementation of this Russian Dolls method by ¨ Ostergard (1), several improvements are presented. Some of them are adaptations of techniques already employed successfully to this problem, like the use of approximate coloring for pruning and bit-parallel operations. Three different coloring heuristics are tested: the standard greedy and two others from the literature, namely greedy with recoloring and fractional coloring. Other improvements directly concern the Russian Dolls scheme: recursive calls where each subproblem (doll) is solved itself by a Russian Dolls Search, application of an elimination rule allowing not to generate a significant number of dolls. Results of computational experiments show that the algorithm outperforms the best exact combinatorial algorithms in the literature for the great majority of the instances tested, being more than twice faster in several cases.

Connected through hyperedge HE-1 (induced by source paper "empirical algorithmics draw your own conclusions"):
  with members:
    - "exact algorithms for maximum clique a computational study"
    - "exact algorithms for maximum clique a computational study"

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)