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 "the complexity of possible winners on partial chains"):
  Abstract: The Possible Winner (PW) problem, a fundamental algorithmic problem in computational social choice, concerns elections where voters express only partial preferences between candidates. Via a sequence of investigations, a complete classification of the complexity of the PW problem was established for all pure positional scoring rules: the PW problem is in P for the plurality and veto rules, and NP-complete for all other such rules. More recently, the PW problem was studied on classes of restricted partial orders that arise in natural settings, such as partitioned partial orders and truncated partial orders; in particular, it was shown that there are rules for which the PW problem drops from NP-complete to P on such restricted partial orders. Here, we investigate the PW problem on partial chains, i.e., partial orders that are a total order on a subset of their domains. Such orders arise naturally in a variety of settings, including rankings of movies or restaurants. We classify the complexity of the PW problem on partial chains by establishing that, perhaps surprisingly, this restriction does not change the complexity of the problem, namely, the PW problem is NP-complete for all pure positional scoring rules other than the plurality and veto rules. As a byproduct, we obtain a new and more principled proof of the complexity of the PW problem on arbitrary partial orders.

Includes members:
  Member "computational social choice meets databases":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "social choice methods for database aggregation")
  Member "the complexity of the possible winner problem over partitioned preferences":
    also connected through other hyperedges:
      (none)
  Member "on the exact amount of missing information that makes finding possible winners hard":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a parameterized perspective on protecting elections")
  Member "complexity of manipulation with partial information in voting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "manipulating districts to win elections fine grained complexity")
  Member "riffled independence for efficient inference with partial rankings":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "supporting hard queries over probabilistic preferences")
  Member "determining possible and necessary winners under common voting rules given partial orders":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a parameterized perspective on protecting elections")
  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-6 (induced by source paper "incomplete preferences in single peaked electorates")
  Member "complexity of and algorithms for borda manipulation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "byzantine preferential 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)