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: "controlled non uniform random generation of decomposable structures"
  Abstract: Consider a class of decomposable combinatorial structures, using different types of atoms Z={Z"1,...,Z"|"Z"|}. We address the random generation of such structures with respect to a size n and a targeted distribution in k of its distinguished atoms. We consider two variations on this problem. In the first alternative, the targeted distribution is given by k real numbers @m"1,...,@m"k such that 0 =0 is the number of undistinguished atoms. The structures must be generated uniformly among the set of structures of size n that contain exactlyn"i atoms Z"i ([email protected][email protected]?k). We give a O(r^[email protected]?"i"="1^kn"i^2+mnklogn) algorithm for generating m structures, which simplifies into a O([email protected]?"i"="1^kn"i+mn) for regular specifications.

Connected through hyperedge HE-1 (induced by source paper "random bit optimal uniform sampling for rooted planar trees with given sequence of degrees and applications"):
  with members:
    - "multi dimensional boltzmann sampling of languages"

Connected through hyperedge HE-2 (induced by source paper "path computation in multi layer multi domain networks a language theoretic approach"):
  with members:
    - "weighted random generation of context free languages analysis of collisions in random urn occupancy models"

Connected through hyperedge HE-3 (induced by source paper "non redundant random generation algorithms for weighted context free languages"):
  with members:
    - "multi dimensional boltzmann sampling of languages"
    - "on the average complexity of moore s state minimization algorithm"
    - "uniform random sampling of traces in very large models"

Connected through hyperedge HE-4 (induced by source paper "the weighted words collector"):
  with members:
    - "multi dimensional boltzmann sampling of languages"
    - "weighted random generation of context free languages analysis of collisions in random urn occupancy models"

Connected through hyperedge HE-5 (induced by source paper "rule weighted and terminal weighted context free grammars have identical expressivity"):
  with members:
    - "multi dimensional boltzmann sampling of languages"

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)