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: "heuristic rating estimation approach to the pairwise comparisons method"
  Abstract: The Heuristic Ratio Estimation (HRE) approach proposes a new way of using the pairwise comparisons matrix. It allows the assumption that the weights of some alternatives (herein referred to as concepts) are known and fixed, hence the weight vector needs to be estimated only for the other unknown values. The main purpose of this paper is to extend the previously proposed iterative HRE algorithm and present all the heuristics that create a generalized approach. Theoretical considerations are accompanied by a few numerical examples demonstrating how the selected heuristics can be used in practice.

Connected through hyperedge HE-1 (induced by source paper "when condition of order preservation is met"):
  with members:
    - "notes on order preservation and consistency in ahp"
    - "on the properties of the priority deriving procedure in the pairwise comparisons method"
    - "heuristic rating estimation geometric approach"
    - "on axiomatization of inconsistency indicators for pairwise comparisons"

Connected through hyperedge HE-2 (induced by source paper "when is the condition of order preservation met"):
  with members:
    - "notes on order preservation and consistency in ahp"
    - "on the properties of the priority deriving procedure in the pairwise comparisons method"
    - "heuristic rating estimation geometric approach"
    - "on axiomatization of inconsistency indicators for pairwise comparisons"

Connected through hyperedge HE-3 (induced by source paper "notes on the existence of a solution in the pairwise comparisons method using the heuristic rating estimation approach"):
  with members:
    - "managing null entries in pairwise comparisons"
    - "on axiomatization of inconsistency indicators for pairwise comparisons"
    - "on distance based inconsistency reduction algorithms for pairwise comparisons"

Connected through hyperedge HE-4 (induced by source paper "on the properties of the priority deriving procedure in the pairwise comparisons method"):
  with members:
    - "notes on order preservation and consistency in ahp"
    - "heuristic rating estimation geometric approach"
    - "on axiomatization of inconsistency indicators for pairwise comparisons"
    - "on distance based inconsistency reduction algorithms for pairwise comparisons"

Connected through hyperedge HE-5 (induced by source paper "notes on order preservation and consistency in ahp"):
  with members:
    - "heuristic rating estimation geometric approach"
    - "managing null entries in pairwise comparisons"
    - "on distance based inconsistency reduction algorithms for pairwise comparisons"

Connected through hyperedge HE-6 (induced by source paper "heuristic rating estimation geometric approach"):
  with members:
    - "notes on the existence of a solution in the pairwise comparisons method using the heuristic rating estimation approach"
    - "axiomatic properties of inconsistency indices for pairwise comparisons"
    - "on distance based inconsistency reduction algorithms for pairwise comparisons"

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)