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: "point line cover the easy kernel is essentially tight"
  Abstract: The input to the NP-hard Point Line Cover problem (PLC) consists of a set $P$ of $n$ points on the plane and a positive integer $k$, and the question is whether there exists a set of at most $k$ lines which pass through all points in $P$. A simple polynomial-time reduction reduces any input to one with at most $k^2$ points. We show that this is essentially tight under standard assumptions. More precisely, unless the polynomial hierarchy collapses to its third level, there is no polynomial-time algorithm that reduces every instance $(P,k)$ of PLC to an equivalent instance with $O(k^{2-\epsilon})$ points, for any $\epsilon>0$. This answers, in the negative, an open problem posed by Lokshtanov (PhD Thesis, 2009). #R##N#Our proof uses the machinery for deriving lower bounds on the size of kernels developed by Dell and van Melkebeek (STOC 2010). It has two main ingredients: We first show, by reduction from Vertex Cover, that PLC---conditionally---has no kernel of total size $O(k^{2-\epsilon})$ bits. This does not directly imply the claimed lower bound on the number of points, since the best known polynomial-time encoding of a PLC instance with $n$ points requires $\omega(n^{2})$ bits. To get around this we build on work of Goodman et al. (STOC 1989) and devise an oracle communication protocol of cost $O(n\log n)$ for PLC; its main building block is a bound of $O(n^{O(n)})$ for the order types of $n$ points that are not necessarily in general position, and an explicit algorithm that enumerates all possible order types of n points. This protocol and the lower bound on total size together yield the stated lower bound on the number of points. #R##N#While a number of essentially tight polynomial lower bounds on total sizes of kernels are known, our result is---to the best of our knowledge---the first to show a nontrivial lower bound for structural/secondary parameters.

Connected through hyperedge HE-1 (induced by source paper "dynamic complexity meets parameterised algorithms"):
  with members:
    - "on the descriptive complexity of color coding"
    - "reoptimization of parameterized problems"
    - "a strategy for dynamic programs start over and muddle through"
    - "dynamic parameterized problems and algorithms"
    - "fast parallel fixed parameter algorithms via color coding"
    - "reachability is in dynfo"

Connected through hyperedge HE-2 (induced by source paper "variable elimination in binary csps"):
  with members:
    - "on singleton arc consistency for csps defined by monotone patterns"
    - "variable and value elimination in binary constraint satisfaction via forbidden patterns"
    - "hybrid tractable classes of binary quantified constraint satisfaction problems"
    - "solving functional constraints by variable substitution"

Connected through hyperedge HE-3 (induced by source paper "optimal data reduction for graph coloring using low degree polynomials"):
  with members:
    - "smaller parameters for vertex cover kernelization"
    - "fine grained parameterized complexity analysis of graph coloring problems"
    - "optimal sparsification for some binary csps using low degree polynomials"
    - "how much does a treedepth modulator help to obtain polynomial kernels beyond sparse graphs"
    - "sparsification upper and lower bounds for graph problems and not all equal sat"
    - "data reduction for graph coloring problems"
    - "list h coloring a graph by removing few vertices"
    - "kernelization lower bounds by cross composition"

Connected through hyperedge HE-4 (induced by source paper "best case and worst case sparsifiability of boolean csps"):
  with members:
    - "optimal data reduction for graph coloring using low degree polynomials"
    - "which np hard sat and csp problems admit exponentially improved algorithms"
    - "kernelization of constraint satisfaction problems a study through universal algebra"
    - "optimal sparsification for some binary csps using low degree polynomials"
    - "sparsification upper and lower bounds for graph problems and not all equal sat"
    - "on sparsification for computing treewidth"
    - "weak bases of boolean co clones"
    - "kernelization lower bounds by cross composition"

Connected through hyperedge HE-5 (induced by source paper "dynamic parameterized problems and algorithms"):
  with members:
    - "fully dynamic maximal matching in constant update time"
    - "fully dynamic connectivity in o log n log log n 2 amortized expected time"
    - "linear time kernelization for feedback vertex set"
    - "a linear time parameterized algorithm for directed feedback vertex set"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "dynamic graph connectivity with improved worst case update time and sublinear space"
    - "improved algorithms for decremental single source reachability on directed graphs"
    - "fast dynamic graph algorithms for parameterized problems"

Connected through hyperedge HE-6 (induced by source paper "a practical algorithm for enumerating collinear points"):
  with members:
    - "finding points in general position"

Connected through hyperedge HE-7 (induced by source paper "an improved lower bound for general position subset selection"):
  with members:
    - "finding points in general position"

Connected through hyperedge HE-8 (induced by source paper "frameworks for solving turing kernel lower bound problem and finding natural candidate problems in np intermediate"):
  with members:
    - "turing kernelization for finding long paths and cycles in restricted graph classes"
    - "abusing the tutte matrix an algebraic instance compression for the k set cycle problem"
    - "kernelization lower bounds by cross composition"
    - "non existence of polynomial kernels for the test cover problem"
    - "kernelization of packing problems"
    - "clique cover and graph separation new incompressibility results"
    - "co nondeterminism in compositions a kernelization lower bound for a ramsey type problem"
    - "vertex cover kernelization revisited upper and lower bounds for a refined parameter"

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)