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: "inconsistency in the ordinal pairwise comparisons method with and without ties"
  Abstract: Abstract   Comparing alternatives in pairs is a well-known method used to create ranking. Experts are asked to perform a series of binary comparisons and then, using mathematical methods, the final ranking is constructed. Experts conduct a series of single assessments, however, they may not always be consistent. The level of inconsistency among individual assessments is widely accepted as a measure of the ranking quality. The higher the ranking quality, the higher its credibility. One of the earliest and most widespread inconsistency indices is the consistency coefficient defined by Kendall and Babington Smith. In their work, the authors consider binary pairwise comparisons, i.e., those where the result of an individual comparison can only be better or worse.  In the presented work, the maximal number of inconsistent triads in the set of ordinal pairwise comparisons with ties of arbitrary size is determined (formula 14). This, in turn, opens the possibility of effectively extending the Kendall and Babington Smith index to pairwise comparisons, where the result of an individual comparison can be: better, worse or equal. Hence, this effectively extends the use of this index to the Analytic Hierarchy Process and other quantitative methods based on comparing alternatives in pairs. The work also introduces the notions of a generalized tournament and a double tournament as graphs that model ordinal pairwise comparisons with ties and the maximally inconsistent set of pairwise comparisons with ties, respectively. The relationship between the most inconsistent set of pairwise comparisons with ties and the set cover problem is also shown.

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"
    - "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 the properties of the priority deriving procedure in the pairwise comparisons method"
    - "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:
    - "on normalization of inconsistency indicators in pairwise comparisons"
    - "on the properties of the priority deriving procedure in the pairwise comparisons method"
    - "heuristic rating estimation geometric approach"

Connected through hyperedge HE-3 (induced by source paper "towards quantification of incompleteness in the pairwise comparisons method"):
  with members:
    - "notes on the existence of a solution in the pairwise comparisons method using the heuristic rating estimation approach"
    - "on axiomatization of inconsistency indicators 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)