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: "proportional approval voting harmonic k median and negative association"
  Abstract: We study Proportional Approval Voting (PAV)---an election system used for choosing representatives bodies, such as parliaments, based on preferences of a population of voters over individual candidates. We observe that the problem of computing the outcome of PAV can be cast as a variant of the standard k-median problem. Our main result is that, due to the specific (harmonic) cost structure, the problem allows constant factor approximation that does not require the underlying connection costs to be metric. To the best of our knowledge this is the first constant factor approximation algorithm for a facility location type problem not assuming triangle inequalities for connection costs. #R##N#The algorithm we propose is a standard dependent rounding routine [Srinivasan FOCS'01] applied to the solution of a natural LP-relaxation of the problem. The rounding process is well known to produce distributions over integral solutions satisfying Negative Correlation (NC). This, however, is not sufficient for our analysis. We show that, if the rounding process follows a predefined tournament tree, dependent rounding has a stronger property that we call Binary Negative Association (BNA). We also show that if the pairs of elements to be correlated are being selected by an adaptive adversary, then the BNA may not hold, while the proof of NC does not depend on the order of selection of elements. We believe the BNA property of dependent rounding is of independent interest and that it may find applications in other settings.

Connected through hyperedge HE-1 (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"

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.DS(Data Structures and Algorithms)