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 "finding all convex cuts of a plane graph in polynomial time"):
  Abstract: Convexity is a notion that has been defined for subsets of R n and for subsets of general graphs. A convex cut of a graph G = (V,E) is a 2-partition V1 u [V2 = V such that both V1 and V2 are convex, i. e., shortest paths between vertices in Vi never leave Vi, i 2 {1,2}. Finding convex cuts is NP-hard for general graphs. To characterize convex cuts, we employ the Djokovic relation, a reflexive and symmetric relation on the edges of a graph that is based on shortest paths between the edges’ end vertices. It is known for a long time that, if G is bipartite and the Djokovic relation is transitive on G, i. e., G is a partial cube, then the cut-sets of G’s convex cuts are precisely the equivalence classes of the Djokovic relation. In particular, any edge of G is contained in the cut-set of exactly one convex cut. We first characterize a class of plane graphs that we call well-arranged. These graphs are not necessarily partial cubes, but any edge of a well-arranged graph is contained in the cut-set(s) of at least one convex cut. Moreover, the cuts can be embedded into the plane such that they form an arrangement of pseudolines, or a slight generalization thereof. Although a well-arranged graph G is not necessarily a partial cube, there always exists a partial cube that contains a subdivision of G. We also present an algorithm that uses the Djokovic relation for computing all convex cuts of a (not necessarily plane) bipartite graph in O(|E| 3 ) time. Specifically, a cut-set is the cut-set of a convex cut if and only if the Djokovic relation holds for any pair of edges in the cut-set. We then characterize the cut-sets of the convex cuts of a general graph H using two binary relations on edges: (i) the Djokovic relation on the edges of a subdivision of H, where any edge of H is subdivided into exactly two edges and (ii) a relation on the edges of H itself that is not the Djokovic relation. Finally, we use this characterization to present the first algorithm for finding all convex cuts of a plane graph in polynomial time.

Includes members:
  Member "recent advances in graph partitioning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multilevel acyclic hypergraph partitioning")
  Member "algorithms for generating convex sets in acyclic digraphs":
    also connected through other hyperedges:
      (none)

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.DS(Data Structures and Algorithms)