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: "on the properties of the priority deriving procedure in the pairwise comparisons method"
  Abstract: The pairwise comparisons method can be used when the relative order of preferences among different concepts (alternatives) needs to be determined. There are several popular imple- mentations of this method, including the Eigenvector Method, the Least Squares Method, the Chi Squares Method and others. Each of the above methods comes with one or more inconsistency in- dices that help to decide whether the consistency of input guarantees obtaining a reliable output, thus taking the optimal decision. This article explores the relationship between inconsistency of input and error of output. An error describes to what extent the obtained results correspond to the single expert's assessments. On the basis of the inconsistency and the error, two properties of the weight deriving procedure are formulated. These properties are proven for eigenvector method and Koczkodaj's inconsistency index. Several estimates using Koczkodaj's inconsistency index for a principal eigenvalue, Saaty's inconsistency index and the Condition of Order Preservation are also provided.

Connected through hyperedge HE-1 (induced by source paper "inconsistency indices for incomplete pairwise comparisons matrices"):
  with members:
    - "on the geometric mean method for incomplete pairwise comparisons"
    - "inconsistency in the ordinal pairwise comparisons method with and without ties"
    - "notes on the existence of a solution in the pairwise comparisons method using the heuristic rating estimation approach"
    - "new results on inconsistency indices and their relationship with the quality of priority vector estimation"
    - "recent advances on inconsistency indices for pairwise comparisons a commentary"
    - "axiomatic properties of inconsistency indices for pairwise comparisons"
    - "on axiomatization of inconsistency indicators for pairwise comparisons"

Connected through hyperedge HE-2 (induced by source paper "on the geometric mean method for incomplete pairwise comparisons"):
  with members:
    - "inconsistency in the ordinal pairwise comparisons method with and without ties"
    - "on normalization of inconsistency indicators in pairwise comparisons"
    - "heuristic rating estimation geometric approach"

Connected through hyperedge HE-3 (induced by source paper "when condition of order preservation is met"):
  with members:
    - "notes on order preservation and consistency in ahp"
    - "heuristic rating estimation geometric approach"
    - "heuristic rating estimation approach to the pairwise comparisons method"
    - "on axiomatization of inconsistency indicators for pairwise comparisons"

Connected through hyperedge HE-4 (induced by source paper "when is the condition of order preservation met"):
  with members:
    - "notes on order preservation and consistency in ahp"
    - "heuristic rating estimation geometric approach"
    - "heuristic rating estimation approach to the pairwise comparisons method"
    - "on axiomatization of inconsistency indicators for pairwise comparisons"

Connected through hyperedge HE-5 (induced by source paper "inconsistency in the ordinal pairwise comparisons method with and without ties"):
  with members:
    - "heuristic rating estimation geometric approach"
    - "an lp based inconsistency monitoring of pairwise comparison matrices"

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)