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 "taking the final step to a full dichotomy of the possible winner problem in pure scoring rules"):
  Abstract: The Possible Winner problem asks, given an election where the voters' preferences over the candidates are specified only partially, whether a designated candidate can become a winner by suitably extending all the votes. Betzler and Dorn [1] proved a result that is only one step away from a full dichotomy of this problem for the important class of pure scoring rules in the case of unweighted voters and an unbounded number of candidates: Possible Winner is NP-complete for all pure scoring rules except plurality, veto, and the scoring rule with vector (2,1,...,1,0), but is solvable in polynomial time for plurality and veto. We take the final step to a full dichotomy by showing that Possible Winner is NP-complete also for the scoring rule with vector (2,1,...,1,0).

Includes members:
  Member "determining possible and necessary winners under common voting rules given partial orders":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the complexity of possible winners on partial chains")
  Member "manipulation of nanson s and baldwin s rules":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "detecting possible manipulators in elections")
  Member "complexity of and algorithms for borda manipulation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the complexity of possible winners on partial chains")
  Member "towards a dichotomy for the possible winner problem in elections based on scoring rules":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the complexity of possible winners on partial chains")
  Member "towards a dichotomy of finding possible winners in elections based on scoring rules":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "complexity of manipulation with partial information in voting")
  Member "a richer understanding of the complexity of election systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "computational social choice and computational complexity bffs")
  Member "dichotomy for voting systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the complexity of online bribery in sequential elections")

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.CC(Computational Complexity)