human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "complexity of shift bribery in committee elections"):
  Abstract: We study the (parameterized) complexity of SHIFT BRIBERY for multiwinner voting rules. We focus on SNTV, Bloc, k-Borda, and Chamberlin-Courant, as well as on approximate variants of Chamberlin-Courant, since the original rule is NP-hard to compute. We show that SHIFT BRIBERY tends to be significantly harder in the multiwinner setting than in the single-winner one by showing settings where SHIFT BRIBERY is easy in the single-winner cases, but is hard (and hard to approximate) in the multiwinner ones. Moreover, we show that the non-monotonicity of those rules which are based on approximation algorithms for the Chamberlin-Courant rule sometimes affects the complexity of SHIFT BRIBERY.

Includes members:
  Member "algorithms for destructive shift bribery":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "local distance restricted bribery in voting")
  Member "the condorcet principle for multiwinner elections from shortlisting to proportionality":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "proportionally representative participatory budgeting with ordinal preferences")
  Member "robustness among multiwinner voting rules":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "matchings under preferences strength of stability and trade offs")
  Member "prices matter for the parameterized complexity of shift bribery":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimal bribery in voting")
  Member "campaign management under approval driven voting rules":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "approximation and hardness of shift bribery")
  Member "properties of multiwinner voting rules":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "who is in your top three optimizing learning in elections with many candidates")
  Member "finding a collective set of items from proportional multirepresentation to group recommendation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "evaluating approval based multiwinner voting in terms of robustness to noise")
  Member "justified representation in approval based committee voting":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "participatory budgeting models and approaches")

Question: Please tell me which class the source paper 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.AI(Artificial Intelligence)