human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "a control dichotomy for pure scoring rules"
  Abstract: Scoring systems are an extremely important class of election systems. A length-$m$ (so-called) scoring vector applies only to $m$-candidate elections. To handle general elections, one must use a family of vectors, one per length. The most elegant approach to making sure such families are "family-like" is the recently introduced notion of (polynomial-time uniform) pure scoring rules [Betzler and Dorn 2010], where each scoring vector is obtained from its precursor by adding one new coefficient. We obtain the first dichotomy theorem for pure scoring rules for a control problem. In particular, for constructive control by adding voters (CCAV), we show that CCAV is solvable in polynomial time for $k$-approval with $k \leq 3$, $k$-veto with $k \leq 2$, every pure scoring rule in which only the two top-rated candidates gain nonzero scores, and a particular rule that is a "hybrid" of 1-approval and 1-veto. For all other pure scoring rules, CCAV is NP-complete. We also investigate the descriptive richness of different models for defining pure scoring rules, proving how more rule-generation time gives more rules, proving that rationals give more rules than do the natural numbers, and proving that some restrictions previously thought to be "w.l.o.g." in fact do lose generality.

Connected through hyperedge HE-1 (induced by source paper "high multiplicity election problems"):
  with members:
    - "the complexity of succinct elections"
    - "complexity dichotomies for unweighted scoring rules"
    - "polynomiality for bin packing with a constant number of item types"
    - "weighted electoral control"
    - "the complexity of online manipulation of sequential elections"
    - "complexity of and algorithms for borda manipulation"
    - "towards a dichotomy for the possible winner problem in elections based on scoring rules"
    - "the shield that never was societies with single peaked preferences are more open to manipulation and control"

Connected through hyperedge HE-2 (induced by source paper "complexity dichotomies for unweighted scoring rules"):
  with members:
    - "weighted electoral control"
    - "control complexity in bucklin fallback and plurality voting an experimental approach"
    - "taking the final step to a full dichotomy of the possible winner problem in pure scoring rules"
    - "complexity of and algorithms for borda manipulation"
    - "where are the hard manipulation problems"
    - "towards a dichotomy of finding possible winners in elections based on scoring rules"
    - "how hard is bribery in elections"

Connected through hyperedge HE-3 (induced by source paper "weighted electoral control"):
  with members:
    - "possible winners in noisy elections"
    - "control in the presence of manipulators cooperative and competitive cases"
    - "schulze and ranked pairs voting are fixed parameter tractable to bribe manipulate and control"
    - "how many vote operations are needed to manipulate a voting system"
    - "control complexity in bucklin fallback and plurality voting an experimental approach"
    - "an atypical survey of typical case heuristic algorithms"
    - "new candidates welcome possible winners with respect to the addition of new candidates"
    - "the complexity of manipulative attacks in nearly single peaked electorates"

Question: Please tell me which class the center node 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)