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: "kernelization complexity of possible winner and coalitional manipulation problems in voting"
  Abstract: In the Possible Winner problem in computational social choice theory, we are given a set of partial preferences and the question is whether a distinguished candidate could be made winner by extending the partial preferences to linear preferences. Previous work has provided, for many common voting rules, fixed parameter tractable algorithms for the Possible Winner problem, with number of candidates as the parameter. However, the corresponding kernelization question is still open and in fact, has been mentioned as a key research challenge. In this paper, we settle this open question for many common voting rules. #R##N#We show that the Possible Winner problem for maximin, Copeland, Bucklin, ranked pairs, and a class of scoring rules that include the Borda voting rule do not admit a polynomial kernel with the number of candidates as the parameter. We show however that the Coalitional Manipulation problem which is an important special case of the Possible Winner problem does admit a polynomial kernel for maximin, Copeland, ranked pairs, and a class of scoring rules that includes the Borda voting rule, when the number of manipulators is polynomial in the number of candidates. A significant conclusion of our work is that the Possible Winner problem is harder than the Coalitional Manipulation problem since the Coalitional Manipulation problem admits a polynomial kernel whereas the Possible Winner problem does not admit a polynomial kernel.

Connected through hyperedge HE-1 (induced by source paper "manipulating districts to win elections fine grained complexity"):
  with members:
    - "complexity of manipulation with partial information in voting"
    - "optimal parameterized algorithms for planar facility location problems using voronoi diagrams"
    - "the complexity of manipulative attacks in nearly single peaked electorates"
    - "anyone but him the complexity of precluding an alternative"

Connected through hyperedge HE-2 (induced by source paper "a parameterized perspective on protecting elections"):
  with members:
    - "optimal bribery in voting"
    - "manipulative elicitation a new attack on elections with incomplete preferences"
    - "on the exact amount of missing information that makes finding possible winners hard"
    - "complexity of manipulation with partial information in voting"
    - "frugal bribery in voting"
    - "elections with few voters candidate control can be easy"
    - "detecting possible manipulators in elections"
    - "more natural models of electoral control by partition"

Connected through hyperedge HE-3 (induced by source paper "manipulative elicitation a new attack on elections with incomplete preferences"):
  with members:
    - "on the exact amount of missing information that makes finding possible winners hard"
    - "elicitation for preferences single peaked on trees"
    - "preference elicitation for single crossing domain"
    - "query complexity of tournament solutions"
    - "complexity of manipulation with partial information in voting"
    - "estimating the margin of victory of an election using sampling"
    - "frugal bribery in voting"
    - "detecting possible manipulators in elections"

Connected through hyperedge HE-4 (induced by source paper "complexity of manipulation with partial information in voting"):
  with members:
    - "manipulative elicitation a new attack on elections with incomplete preferences"
    - "on the exact amount of missing information that makes finding possible winners hard"
    - "complexity of manipulation in elections with partial votes"
    - "frugal bribery in voting"
    - "detecting possible manipulators in elections"
    - "the computational impact of partial votes on strategic voting"
    - "possible and necessary winner problem in social polls"
    - "asymptotic collusion proofness of voting rules the case of large number of candidates"

Connected through hyperedge HE-5 (induced by source paper "frugal bribery in voting"):
  with members:
    - "complexity of manipulation with partial information in voting"
    - "on the hardness of bribery variants in voting with cp nets"
    - "prices matter for the parameterized complexity of shift bribery"
    - "campaign management under approval driven voting rules"
    - "complexity of manipulation bribery and campaign management in bucklin and fallback voting"
    - "dominating manipulations in voting with partial information"
    - "complexity of and algorithms for borda manipulation"
    - "multimode control attacks on elections"

Connected through hyperedge HE-6 (induced by source paper "the control complexity of r approval from the single peaked case to the general case"):
  with members:
    - "computational aspects of nearly single peaked electorates"
    - "are there any nicely structured preference profiles nearby"
    - "facility location with double peaked preference"
    - "election attacks with few candidates"
    - "computational aspects of multi winner approval voting"
    - "the complexity of fully proportional representation for single crossing electorates"
    - "the complexity of manipulative attacks in nearly single peaked electorates"
    - "the complexity of manipulating k approval elections"

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)