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 "election with bribed voter uncertainty hardness and approximation algorithm"):
  Abstract: Bribery in election (or computational social choice in general) is an important problem that has received a considerable amount of attention. In the classic bribery problem, the briber (or attacker) bribes some voters in attempting to make the briber's designated candidate win an election. In this paper, we introduce a novel variant of the bribery problem, "Election with Bribed Voter Uncertainty" or BVU for short, accommodating the uncertainty that the vote of a bribed voter may or may not be counted. This uncertainty occurs either because a bribed voter may not cast its vote in fear of being caught, or because a bribed voter is indeed caught and therefore its vote is discarded. As a first step towards ultimately understanding and addressing this important problem, we show that it does not admit any multiplicative $O(1)$-approximation algorithm modulo standard complexity assumptions. We further show that there is an approximation algorithm that returns a solution with an additive-$\epsilon$ error in FPT time for any fixed $\epsilon$.

Includes members:
  Member "when the cookie meets the blockchain privacy risks of web payments via cryptocurrencies":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sok blockchain technology and its potential use cases")
  Member "possible winners in noisy elections":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "weighted electoral control")
  Member "complexity of manipulation bribery and campaign management in bucklin and fallback voting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal bribery in voting")
  Member "determining possible and necessary winners under common voting rules given partial orders":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the complexity of possible winners on partial chains")
  Member "taking the final step to a full dichotomy of the possible winner problem in pure scoring rules":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the complexity of possible winners on partial chains")
  Member "multimode control attacks on elections":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the complexity of constructive control under nearly single peaked preferences")
  Member "the complexity of manipulating k approval elections":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the complexity of constructive control under nearly single peaked preferences")
  Member "towards a dichotomy for the possible winner problem in elections based on scoring rules":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "the complexity of possible winners on partial chains")

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.DS(Data Structures and Algorithms)