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: "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.

Connected through hyperedge HE-1 (induced by source paper "peeking behind the ordinal curtain improving distortion via cardinal queries"):
  with members:
    - "improved metric distortion for deterministic social choice rules"
    - "the distortion of distributed voting"
    - "awareness of voter passion greatly improves the distortion of metric social choice"
    - "approval based elections and distortion of voting rules"
    - "an analysis framework for metric voting based on lp duality"
    - "on the distortion value of the elections with abstention"
    - "random dictators with a random referee constant sample complexity mechanisms for social choice"
    - "relating metric distortion and fairness of social choice rules"

Connected through hyperedge HE-2 (induced by source paper "awareness of voter passion greatly improves the distortion of metric social choice"):
  with members:
    - "improved metric distortion for deterministic social choice rules"
    - "the distortion of distributed voting"
    - "manipulating elections by selecting issues"
    - "peeking behind the ordinal curtain improving distortion via cardinal queries"
    - "approval based elections and distortion of voting rules"
    - "on the distortion value of the elections with abstention"
    - "random dictators with a random referee constant sample complexity mechanisms for social choice"
    - "relating metric distortion and fairness of social choice rules"

Connected through hyperedge HE-3 (induced by source paper "improved metric distortion for deterministic social choice rules"):
  with members:
    - "relating metric distortion and fairness of social choice rules"
    - "tradeoffs between information and ordinal approximation for bipartite matching"
    - "of the people voting is more effective with representative candidates"
    - "on the distortion of voting with multiple representative candidates"
    - "metric distortion of social choice rules lower bounds and fairness properties"
    - "randomized social choice functions under metric preferences"
    - "on voting and facility location"

Connected through hyperedge HE-4 (induced by source paper "favorite candidate voting for eliminating the least popular candidate in metric spaces"):
  with members:
    - "what do multiwinner voting rules do an experiment over the two dimensional euclidean domain"
    - "improved metric distortion for deterministic social choice rules"
    - "awareness of voter passion greatly improves the distortion of metric social choice"
    - "metric distortion of social choice rules lower bounds and fairness properties"
    - "randomized social choice functions under metric preferences"
    - "on voting and facility location"

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.MA(Multiagent Systems)