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: "eliciting single peaked preferences using comparison queries"
  Abstract: Voting is a general method for aggregating the preferences of multiple agents. Each agent ranks all the possible alternatives, and based on this, an aggregate ranking of the alternatives (or at least a winning alternative) is produced. However, when there are many alternatives, it is impractical to simply ask agents to report their complete preferences. Rather, the agents' preferences, or at least the relevant parts thereof, need to be elicited. This is done by asking the agents a (hopefully small) number of simple queries about their preferences, such as comparison queries, which ask an agent to compare two of the alternatives. Prior work on preference elicitation in voting has focused on the case of unrestricted preferences. It has been shown that in this setting, it is sometimes necessary to ask each agent (almost) as many queries as would be required to determine an arbitrary ranking of the alternatives. In contrast, in this paper, we focus on single-peaked preferences. We show that such preferences can be elicited using only a linear number of comparison queries, if either the order with respect to which preferences are single-peaked is known, or at least one other agent's complete preferences are known. We show that using a sublinear number of queries does not suffice. We also consider the case of cardinally single-peaked preferences. For this case, we show that if the alternatives' cardinal positions are known, then an agent's preferences can be elicited using only a logarithmic number of queries; however, we also show that if the cardinal positions are not known, then a sublinear number of queries does not suffice. We present experimental results for all elicitation algorithms. We also consider the problem of only eliciting enough information to determine the aggregate ranking, and show that even for this more modest objective, a sublinear number of queries per agent does not suffice for known ordinal or unknown cardinal positions. Finally, we discuss whether and how these techniques can be applied when preferences are almost single-peaked.

Connected through hyperedge HE-1 (induced by source paper "swap dynamics in single peaked house markets"):
  with members:
    - "minimal envy and popular matchings"
    - "optimal reallocation under additive and ordinal preferences"
    - "fair assignment of indivisible objects under ordinal preferences"
    - "extremal behaviour in multiagent contract negotiation"

Connected through hyperedge HE-2 (induced by source paper "incomplete preferences in single peaked electorates"):
  with members:
    - "on the likelihood of single peaked preferences"
    - "computational aspects of nearly single peaked electorates"
    - "recognising multidimensional euclidean preferences"
    - "modeling single peakedness for votes with ties"
    - "single peaked consistency for weak orders is easy"
    - "reinstating combinatorial protections for manipulation and bribery in single peaked and nearly single peaked electorates"
    - "the one dimensional euclidean domain finitely many obstructions are not enough"
    - "complexity of manipulative actions when voting with ties"

Connected through hyperedge HE-3 (induced by source paper "communication distortion and randomness in metric voting"):
  with members:
    - "comparing election methods where each voter ranks only few candidates"
    - "improved metric distortion for deterministic social choice rules"
    - "approval based elections and distortion of voting rules"
    - "an analysis framework for metric voting based on lp duality"
    - "random dictators with a random referee constant sample complexity mechanisms for social choice"
    - "of the people voting is more effective with representative candidates"
    - "on the distortion of voting with multiple representative candidates"
    - "combinatorial auctions do need modest interaction"

Connected through hyperedge HE-4 (induced by source paper "individual based stability in hedonic diversity games"):
  with members:
    - "convergence and hardness of strategic schelling segregation"
    - "schelling games on graphs"
    - "hedonic diversity games"
    - "on the likelihood of single peaked preferences"
    - "fractional hedonic games"
    - "generating single peaked votes"

Connected through hyperedge HE-5 (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-6 (induced by source paper "computational aspects of nearly single peaked electorates"):
  with members:
    - "on the likelihood of single peaked preferences"
    - "are there any nicely structured preference profiles nearby"
    - "structure in dichotomous preferences"
    - "the control complexity of r approval from the single peaked case to the general case"
    - "on the computation of fully proportional representation"
    - "the complexity of fully proportional representation for single crossing electorates"
    - "the complexity of manipulative attacks in nearly single peaked electorates"
    - "clone structures in voters preferences"

Connected through hyperedge HE-7 (induced by source paper "personalized and situation aware multimodal route recommendations the favour algorithm"):
  with members:
    - "crowdplanner a crowd based route recommendation system"
    - "preference elicitation for general random utility models"

Connected through hyperedge HE-8 (induced by source paper "recognizing and eliciting weakly single crossing profiles on trees"):
  with members:
    - "computational aspects of nearly single peaked electorates"
    - "elicitation for preferences single peaked on trees"
    - "preference elicitation for single crossing domain"
    - "structure in dichotomous preferences"
    - "the single crossing property on a tree"
    - "on the computation of fully proportional representation"
    - "the complexity of fully proportional representation for single crossing electorates"
    - "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)