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 "classes of graphs with low complexity the case of classes with bounded linear rankwidth"):
  Abstract: Classes with bounded rankwidth are MSO-transductions of trees and classes with bounded linear rankwidth are MSO-transductions of paths -- a result that shows a strong link between the properties of these graph classes considered from the point of view of structural graph theory and from the point of view of finite model theory. We take both views on classes with bounded linear rankwidth and prove structural and model theoretic properties of these classes. The structural results we obtain are the following. #R##N#1) The number of unlabeled graphs of order $n$ with linear rank-width at most~$r$ is at most $\bigl[(r/2)!\,2^{\binom{r}{2}}3^{r+2}\bigr]^n$. #R##N#2) Graphs with linear rankwidth at most $r$ are linearly $\chi$-bounded. Actually, they have bounded $c$-chromatic number, meaning that they can be colored with $f(r)$ colors, each color inducing a cograph. #R##N#3) To the contrary, based on a Ramsey-like argument, we prove for every proper hereditary family $F$ of graphs (like cographs) that there is a class with bounded rankwidth that does not have the property that graphs in it can be colored by a bounded number of colors, each inducing a subgraph in $F$. #R##N#From the model theoretical side we obtain the following results: #R##N#1) A direct short proof that graphs with linear rankwidth at most $r$ are first-order transductions of linear orders. This result could also be derived from Colcombet's theorem on first-order transduction of linear orders and the equivalence of linear rankwidth with linear cliquewidth. #R##N#2) For a class $C$ with bounded linear rankwidth the following conditions are equivalent: a) $C$ is stable, b) $C$ excludes some half-graph as a semi-induced subgraph, c) $C$ is a first-order transduction of a class with bounded pathwidth. #R##N#These results open the perspective to study classes admitting low linear rankwidth covers.

Includes members:
  Member "on the number of types in sparse graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "nowhere dense graph classes and algorithmic applications a tutorial at highlights of logic games and automata 2019")
  Member "reconfiguration on sparse graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dominating sets reconfiguration under token sliding")
  Member "deciding first order properties of nowhere dense graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hitting topological minors is fpt")
  Member "solving dominating set in larger classes of graphs fpt algorithms and polynomial kernels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "lossy kernels for connected dominating set on sparse graphs")

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.LO(Logic in Computer Science)