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: "approximating the maxcover problem with bounded frequencies in fpt time"
  Abstract: We study approximation algorithms for several variants of the MaxCover problem, with the focus on algorithms that run in FPT time. In the MaxCover problem we are given a set N of elements, a family S of subsets of N, and an integer K. The goal is to find up to K sets from S that jointly cover (i.e., include) as many elements as possible. This problem is well-known to be NP-hard and, under standard complexitytheoretic assumptions, the best possible polynomial-time approximation algorithm has approximation ratio (1 − 1 ). We first consider a variant of MaxCover with bounded element frequencies, i.e., a variant where there is a constant p such that each element belongs to at most p sets in S. For this case we show that there is an FPT approximation scheme (i.e., for each β there is a β-approximation algorithm running in FPT time) for the problem of maximizing the number of covered elements, and a randomized FPT approximation scheme for the problem of minimizing the number of elements left uncovered (we take K to be the parameter). Then, for the case where there is a constant p such that each element belongs to at least p sets from S, we show that the standard greedy approximation algorithm achieves approximation ratio exactly 1 − e −max(pK/kSk,1) . We conclude by considering an unrestricted variant of MaxCover, and show approximation algorithms that run in exponential time and combine an exact algorithm with a greedy approximation. Some of our results improve currently known results for MaxVertexCover.

Connected through hyperedge HE-1 (induced by source paper "parameterized algorithmics for computational social choice nine research challenges"):
  with members:
    - "computational aspects of nearly single peaked electorates"
    - "prices matter for the parameterized complexity of shift bribery"
    - "are there any nicely structured preference profiles nearby"
    - "campaign management under approval driven voting rules"
    - "the control complexity of r approval from the single peaked case to the general case"
    - "complexity of control behaviors in k peaked elections for a variant of approval voting"
    - "computing socially efficient cake divisions"
    - "confronting intractability via parameters"

Connected through hyperedge HE-2 (induced by source paper "finding a collective set of items from proportional multirepresentation to group recommendation"):
  with members:
    - "generalizing the single crossing property on lines and trees to intermediate preferences on median graphs"
    - "structure in dichotomous preferences"
    - "properties of multiwinner voting rules"
    - "ptas for minimax approval voting"
    - "computational aspects of multi winner approval voting"
    - "on the computation of fully proportional representation"
    - "a social welfare optimal sequential allocation procedure"
    - "the complexity of fully proportional representation for single crossing electorates"

Connected through hyperedge HE-3 (induced by source paper "faster computation of representative families for uniform matroids with applications"):
  with members:
    - "algorithm for finding k vertex out trees and its application to k internal out branching problem"
    - "a linear vertex kernel for maximum internal spanning tree"

Connected through hyperedge HE-4 (induced by source paper "achieving fully proportional representation approximability results"):
  with members:
    - "group activity selection problem"
    - "on the computation of fully proportional representation"
    - "the complexity of fully proportional representation for single crossing electorates"
    - "multimode control attacks on elections"
    - "where are the hard manipulation problems"
    - "guarantees for the success frequency of an algorithm for finding dodgson election winners"
    - "exact complexity of the winner problem for young elections"
    - "exact analysis of dodgson elections lewis carroll s 1876 voting system is complete for parallel access to np"

Connected through hyperedge HE-5 (induced by source paper "the complexity of fully proportional representation for single crossing electorates"):
  with members:
    - "properties of multiwinner voting rules"
    - "on the computation of fully proportional representation"
    - "achieving fully proportional representation is easy in practice"
    - "fully proportional representation as resource allocation approximability results"
    - "the complexity of manipulative attacks in nearly single peaked electorates"
    - "clone structures in voters preferences"

Connected through hyperedge HE-6 (induced by source paper "parameterized approximation schemes using graph widths"):
  with members:
    - "augmenting graphs to minimize the diameter"
    - "parameterized in approximability of subset problems"
    - "not so easy problems for tree decomposable graphs"
    - "the parameterised complexity of list problems on graphs of bounded treewidth"
    - "approximation schemes for steiner forest on planar graphs and graphs of bounded treewidth"

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.DS(Data Structures and Algorithms)