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 "optimal bribery in voting"):
  Abstract: Studying complexity of various bribery problems has been one of the main research focus in computational social choice. In all the models of bribery studied so far, the briber has to pay every voter some amount of money depending on what the briber wants the voter to report and the briber has some budget at her disposal. Although these models successfully capture many real world applications, in many other scenarios, the voters may be unwilling to deviate too much from their true preferences. In this paper, we study the computational complexity of the problem of finding a preference profile which is as close to the true preference profile as possible and still achieves the briber's goal subject to budget constraints. We call this problem Optimal Bribery. We consider three important measures of distances, namely, swap distance, footrule distance, and maximum displacement distance, and resolve the complexity of the optimal bribery problem for many common voting rules. We show that the problem is polynomial time solvable for the plurality and veto voting rules for all the three measures of distance. On the other hand, we prove that the problem is NP-complete for a class of scoring rules which includes the Borda voting rule, maximin, Copeland$^\alpha$ for any $\alpha\in[0,1]$, and Bucklin voting rules for all the three measures of distance even when the distance allowed per voter is $1$ for the swap and maximum displacement distances and $2$ for the footrule distance even without the budget constraints (which corresponds to having an infinite budget). For the $k$-approval voting rule for any constant $k>1$ and the simplified Bucklin voting rule, we show that the problem is NP-complete for the swap distance even when the distance allowed is $2$ and for the footrule distance even when the distance allowed is $4$ even without the budget constraints.

Includes members:
  Member "a unifying framework for manipulation problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "local distance restricted bribery in voting")
  Member "on the hardness of bribery variants in voting with cp nets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "local distance restricted bribery in voting")
  Member "complexity of shift bribery in committee elections":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the complexity of destructive bribery in approval based multi winner voting")
  Member "prices matter for the parameterized complexity of shift bribery":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "local distance restricted bribery in voting")
  Member "frugal bribery in voting":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a parameterized perspective on protecting elections")
  Member "complexity of manipulation bribery and campaign management in bucklin and fallback voting":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "local distance restricted bribery in voting")
  Member "determining possible and necessary winners under common voting rules given partial orders":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the complexity of possible winners on partial chains")
  Member "approximation algorithms for campaign management":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "local distance restricted bribery in voting")

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.GT(Computer Science and Game Theory)