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 "on the approximability of covering points by lines and related problems"):
  Abstract: Given a set $P$ of $n$ points in the plane, {\sc Covering Points by Lines} is the problem of finding a minimum-cardinality set $\L$ of lines such that every point $p \in P$ is incident to some line $\ell \in \L$. As a geometric variant of {\sc Set Cover}, {\sc Covering Points by Lines} is still NP-hard. Moreover, it has been proved to be APX-hard, and hence does not admit any polynomial-time approximation scheme unless P $=$ NP\@. In contrast to the small constant approximation lower bound implied by APX-hardness, the current best approximation ratio for {\sc Covering Points by Lines} is still $O(\log n)$, namely the ratio achieved by the greedy algorithm for {\sc Set Cover}. #R##N#In this paper, we give a lower bound of $\Omega(\log n)$ on the approximation ratio of the greedy algorithm for {\sc Covering Points by Lines}. We also study several related problems including {\sc Maximum Point Coverage by Lines}, {\sc Minimum-Link Covering Tour}, {\sc Minimum-Link Spanning Tour}, and {\sc Min-Max-Turn Hamiltonian Tour}. We show that all these problems are either APX-hard or at least NP-hard. In particular, our proof of APX-hardness of {\sc Min-Max-Turn Hamiltonian Tour} sheds light on the difficulty of {\sc Bounded-Turn-Minimum-Length Hamiltonian Tour}, a problem proposed by Aggarwal et al.\ at SODA 1997.

Includes members:
  Member "qptas for geometric set cover problems via optimal separators":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal parameterized algorithms for planar facility location problems using voronoi diagrams")
  Member "point line cover the easy kernel is essentially tight":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dynamic complexity meets parameterised algorithms")
  Member "tight lower bounds for the size of epsilon nets":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the epsilon t net problem")
  Member "improved approximation algorithms for geometric set cover":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the epsilon t net problem")
  Member "optimal covering tours with turn costs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "minimum scan cover with angular transition costs")

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.CG(Computational Geometry)