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 "ordinal approximation for social choice matching and facility location problems given candidate positions"):
  Abstract: In this work we consider general facility location and social choice problems, in which sets of agents $\mathcal{A}$ and facilities $\mathcal{F}$ are located in a metric space, and our goal is to assign agents to facilities (as well as choose which facilities to open) in order to optimize the social cost. We form new algorithms to do this in the presence of only {\em ordinal information}, i.e., when the true costs or distances from the agents to the facilities are {\em unknown}, and only the ordinal preferences of the agents for the facilities are available. The main difference between our work and previous work in this area is that while we assume that only ordinal information about agent preferences in known, we know the exact locations of the possible facilities $\mathcal{F}$. Due to this extra information about the facilities, we are able to form powerful algorithms which have small {\em distortion}, i.e., perform almost as well as omniscient algorithms but use only ordinal information about agent preferences. For example, we present natural social choice mechanisms for choosing a single facility to open with distortion of at most 3 for minimizing both the total and the median social cost; this factor is provably the best possible. We analyze many general problems including matching, $k$-center, and $k$-median, and present black-box reductions from omniscient approximation algorithms with approximation factor $\beta$ to ordinal algorithms with approximation factor $1+2\beta$; doing this gives new ordinal algorithms for many important problems, and establishes a toolkit for analyzing such problems in the future.

Includes members:
  Member "tradeoffs between information and ordinal approximation for bipartite matching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "peeking behind the ordinal curtain improving distortion via cardinal queries")
  Member "sequential deliberation for social choice":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "aggregation over metric spaces proposing and voting in elections budgeting and legislation")
  Member "of the people voting is more effective with representative candidates":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "peeking behind the ordinal curtain improving distortion via cardinal queries")
  Member "on the distortion of voting with multiple representative candidates":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "peeking behind the ordinal curtain improving distortion via cardinal queries")
  Member "combinatorial secretary problems with ordinal information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the secretary recommendation problem")
  Member "truthful mechanisms for matching and clustering in an ordinal world":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "tradeoffs between information and ordinal approximation for bipartite matching")
  Member "metric distortion of social choice rules lower bounds and fairness properties":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "peeking behind the ordinal curtain improving distortion via cardinal queries")
  Member "truthful facility assignment with resource augmentation an exact analysis of serial dictatorship":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "social cost guarantees in smart route guidance")

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.MA(Multiagent Systems)