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: "axiomatic characterization of committee scoring rules"
  Abstract: Committee scoring rules form a rich class of aggregators of voters' preferences for the purpose of selecting subsets of objects with desired properties, e.g., a shortlist of candidates for an interview, a representative collective body such as a parliament, or a set of locations for a set of public facilities. In the spirit of celebrated Young's characterization result that axiomatizes single-winner scoring rules, we provide an axiomatic characterization of multiwinner committee scoring rules. We show that committee scoring rules---despite forming a remarkably general class of rules---are characterized by the set of four standard axioms, anonymity, neutrality, consistency and continuity, and by one axiom specific to multiwinner rules which we call committee dominance. In the course of our proof, we develop several new notions and techniques. In particular, we introduce and axiomatically characterize multiwinner decision scoring rules, a class of rules that broadly generalizes the well-known majority relation.

Connected through hyperedge HE-1 (induced by source paper "how should we score athletes and candidates geometric scoring rules"):
  with members:
    - "measuring majority power and veto power of voting rules"
    - "consistent approval based multi winner rules"
    - "multiwinner approval rules as apportionment methods"

Connected through hyperedge HE-2 (induced by source paper "committee scoring rules axiomatic characterization and hierarchy"):
  with members:
    - "what do multiwinner voting rules do an experiment over the two dimensional euclidean domain"
    - "the condorcet principle for multiwinner elections from shortlisting to proportionality"
    - "monotonicity axioms in approval based multi winner voting rules"
    - "multiwinner elections with diversity constraints"
    - "consistent approval based multi winner rules"
    - "multiwinner voting with fairness constraints"
    - "group fairness in multiwinner voting"
    - "robustness among multiwinner voting rules"

Connected through hyperedge HE-3 (induced by source paper "equality of voice towards fair representation in crowdsourced top k recommendations"):
  with members:
    - "a unified approach to quantifying algorithmic unfairness measuring individual group unfairness via inequality indices"
    - "beyond parity fairness objectives for collaborative filtering"
    - "multisided fairness for recommendation"
    - "fa ir a fair top k ranking algorithm"
    - "who makes trends understanding demographic biases in crowdsourced recommendations"
    - "properties of multiwinner voting rules"
    - "bpr bayesian personalized ranking from implicit feedback"

Connected through hyperedge HE-4 (induced by source paper "robustness among multiwinner voting rules"):
  with members:
    - "what do multiwinner voting rules do an experiment over the two dimensional euclidean domain"
    - "very hard electoral control problems"
    - "distributed monitoring of election winners"
    - "committee scoring rules axiomatic characterization and hierarchy"
    - "algorithms for destructive shift bribery"
    - "the condorcet principle for multiwinner elections from shortlisting to proportionality"
    - "towards computing victory margins in stv elections"
    - "voting and bribing in single exponential time"

Connected through hyperedge HE-5 (induced by source paper "consistent approval based multi winner rules"):
  with members:
    - "committee scoring rules axiomatic characterization and hierarchy"
    - "consistent probabilistic social choice"
    - "properties of multiwinner voting rules"
    - "finding a collective set of items from proportional multirepresentation to group recommendation"
    - "justified representation in approval based committee voting"
    - "computational aspects of multi winner approval voting"

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.GT(Computer Science and Game Theory)