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: "random crossings in dependency trees"
  Abstract: It has been hypothesized that the rather small number of crossings in real syntactic dependency trees is a side-effect of pressure for dependency length minimization. Here we answer a related important research question: what would be the expected number of crossings if the natural order of a sentence was lost and replaced by a random ordering? We show that this number depends only on the number of vertices of the dependency tree (the sentence length) and the second moment about zero of vertex degrees. The expected number of crossings is minimum for a star tree (crossings are impossible) and maximum for a linear tree (the number of crossings is of the order of the square of the sequence length).

Connected through hyperedge HE-1 (induced by source paper "reappraising the distribution of the number of edge crossings of graphs on a sphere"):
  with members:
    - "edge crossings in random linear arrangements"
    - "a correction on shiloach s algorithm for minimum linear arrangement of trees"

Connected through hyperedge HE-2 (induced by source paper "anti dependency distance minimization in short sequences a graph theoretic approach"):
  with members:
    - "the placement of the head that maximizes predictability an information theoretic approach"
    - "towards a theory of word order comment on dependency distance a new perspective on syntactic patterns in natural language by haitao liu et al"
    - "scarcity of crossing dependencies a direct outcome of a specific constraint"
    - "non crossing dependencies least effort not grammar"
    - "liberating language research from dogmas of the 20th century"
    - "a commentary on the now or never bottleneck a fundamental constraint on language by christiansen and chater 2016"
    - "the risks of mixing dependency lengths from sequences of different length"
    - "hubiness length crossings and their relationships in dependency trees"

Connected through hyperedge HE-3 (induced by source paper "edge crossings in random linear arrangements"):
  with members:
    - "on the maximum crossing number"
    - "crossing patterns in nonplanar road networks"
    - "scarcity of crossing dependencies a direct outcome of a specific constraint"
    - "non crossing dependencies least effort not grammar"
    - "crossings as a side effect of dependency lengths"
    - "liberating language research from dogmas of the 20th century"
    - "a stronger null hypothesis for crossing dependencies"
    - "practical graph isomorphism ii"

Connected through hyperedge HE-4 (induced by source paper "scarcity of crossing dependencies a direct outcome of a specific constraint"):
  with members:
    - "non crossing dependencies least effort not grammar"
    - "crossings as a side effect of dependency lengths"
    - "the risks of mixing dependency lengths from sequences of different length"
    - "a stronger null hypothesis for crossing dependencies"
    - "hubiness length crossings and their relationships in dependency trees"
    - "why sov might be initially preferred and then lost or recovered a theoretical framework"

Connected through hyperedge HE-5 (induced by source paper "crossings as a side effect of dependency lengths"):
  with members:
    - "can chunking reduce syntactic complexity of natural languages"
    - "transition based dependency parsing with stack long short term memory"
    - "the risks of mixing dependency lengths from sequences of different length"
    - "a stronger null hypothesis for crossing dependencies"
    - "the placement of the head that minimizes online memory a complex systems approach"

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.CL(Computation and Language)