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 "edge crossings in random linear arrangements"):
  Abstract: In spatial networks vertices are arranged in some space and edges may cross. When arranging vertices in a 1-dimensional lattice edges may cross when drawn above the vertex sequence as it happens in linguistic and biological networks. Here we investigate the general of problem of the distribution of edge crossings in random arrangements of the vertices. We generalize the existing formula for the expectation of this number in random linear arrangements of trees to any network and derive an expression for the variance of the number of crossings in an arbitrary layout relying on a novel characterization of the algebraic structure of that variance in an arbitrary space. We provide compact formulae for the expectation and the variance in complete graphs, complete bipartite graphs, cycle graphs, one-regular graphs and various kinds of trees (star trees, quasi-star trees and linear trees). In these networks, the scaling of expectation and variance as a function of network size is asymptotically power-law-like in random linear arrangements. Our work paves the way for further research and applications in 1-dimension or investigating the distribution of the number of crossings in lattices of higher dimension or other embeddings.

Includes members:
  Member "on the maximum crossing number":
    also connected through other hyperedges:
      (none)
  Member "crossing patterns in nonplanar road networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the edge crossings of the greedy spanner")
  Member "scarcity of crossing dependencies a direct outcome of a specific constraint":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "anti dependency distance minimization in short sequences a graph theoretic approach")
  Member "non crossing dependencies least effort not grammar":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "anti dependency distance minimization in short sequences a graph theoretic approach")
  Member "crossings as a side effect of dependency lengths":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the relation between dependency distance crossing dependencies and parsing comment on dependency distance a new perspective on syntactic patterns in natural languages by haitao liu et al")
  Member "liberating language research from dogmas of the 20th century":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "anti dependency distance minimization in short sequences a graph theoretic approach")
  Member "a stronger null hypothesis for crossing dependencies":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards a theory of word order comment on dependency distance a new perspective on syntactic patterns in natural language by haitao liu et al")
  Member "random crossings in dependency trees":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reappraising the distribution of the number of edge crossings of graphs on a sphere")

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.DM(Discrete Mathematics)