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: "the multiobjective multidimensional knapsack problem a survey and a new approach"
  Abstract: The knapsack problem (KP) and its multidimensional version (MKP) are basic problems in combinatorial optimization. In this paper we consider their multiobjective extension (MOKP and MOMKP), for which the aim is to obtain or to approximate the set of efficient solutions. In a first step, we classify and describe briefly the existing works, that are essentially based on the use of metaheuristics. In a second step, we propose the adaptation of the two-phase Pareto local search (2PPLS) to the resolution of the MOMKP. With this aim, we use a very-large scale neighborhood (VLSN) in the second phase of the method, that is the Pareto local search. We compare our results to state-of-the-art results and we show that we obtain results never reached before by heuristics, for the biobjective instances. Finally we consider the extension to three-objective instances.

Connected through hyperedge HE-1 (induced by source paper "the 0 1 knapsack problem with qualitative levels"):
  with members:
    - "shortest paths with ordinal weights"

Connected through hyperedge HE-2 (induced by source paper "an efficient primal dual algorithm for fair combinatorial optimization problems"):
  with members:
    - "projection onto the capped simplex"

Connected through hyperedge HE-3 (induced by source paper "modeling and selection of interdependent software requirements using fuzzy graphs"):
  with members:
    - "solving the large scale next release problem with a backbone based multilevel algorithm"
    - "dependency aware software release planning through mining user preferences"
    - "graded causation and defaults"

Connected through hyperedge HE-4 (induced by source paper "many objective pareto local search"):
  with members:
    - "experimental analysis of design elements of scalarizing functions based multiobjective evolutionary algorithms"
    - "nd tree a fast online algorithm for updating a pareto archive and its application in many objective pareto local search"

Connected through hyperedge HE-5 (induced by source paper "enabling complexity performance trade offs for successive cancellation decoding of polar codes"):
  with members:
    - "density evolution for min sum decoding of ldpc codes under unreliable message storage"
    - "on the correlation between polarized becs"
    - "on the construction of polar codes"
    - "polar codes robustness of the successive cancellation decoder with respect to quantization"
    - "how to construct polar codes"
    - "hardware architectures for successive cancellation decoding of polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "performance of ldpc codes under faulty iterative decoding"

Connected through hyperedge HE-6 (induced by source paper "aggregation of composite solutions strategies models examples"):
  with members:
    - "searching a bitstream in linear time for the longest substring of any given density"
    - "restructuring in combinatorial optimization"
    - "towards configuration of applied web based information system"
    - "the exact closest string problem as a constraint satisfaction problem"
    - "solving the maximum agreement subtree and the maximum compatible tree problems on many bounded degree trees"
    - "on the closest string and substring problems"

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)