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: "compression and the origins of zipf s law for word frequencies"
  Abstract: Here we sketch a new derivation of Zipf's law for word frequencies based on optimal coding. The structure of the derivation is reminiscent of Mandelbrot's random typing model but it has multiple advantages over random typing: (1) it starts from realistic cognitive pressures (2) it does not require fine tuning of parameters and (3) it sheds light on the origins of other statistical laws of language and thus can lead to a compact theory of linguistic laws. Our findings suggest that the recurrence of Zipf's law in human languages could originate from pressure for easy and fast communication.

Connected through hyperedge HE-1 (induced by source paper "polysemy and brevity versus frequency in language"):
  with members:
    - "the origins of zipf s meaning frequency law"
    - "the meaning frequency law in zipfian optimization models of communication"

Connected through hyperedge HE-2 (induced by source paper "robustness of sentence length measures in written texts"):
  with members:
    - "in narrative texts punctuation marks obey the same statistics as words"
    - "text mixing shapes the anatomy of rank frequency distributions"
    - "modeling the average shortest path length in growth of word adjacency networks"
    - "punctuation effects in english and esperanto texts"
    - "beyond word frequency bursts lulls and scaling in the temporal distributions of words"

Connected through hyperedge HE-3 (induced by source paper "the placement of the head that maximizes predictability an information theoretic approach"):
  with members:
    - "the polysemy of the words that children learn over time"
    - "kauffman s adjacent possible in word order evolution"
    - "a commentary on the now or never bottleneck a fundamental constraint on language by christiansen and chater 2016"
    - "the placement of the head that minimizes online memory a complex systems approach"

Connected through hyperedge HE-4 (induced by source paper "the origins of zipf s meaning frequency law"):
  with members:
    - "the meaning frequency law in zipfian optimization models of communication"
    - "the optimality of attaching unlinked labels to unlinked meanings"

Connected through hyperedge HE-5 (induced by source paper "a commentary on the now or never bottleneck a fundamental constraint on language by christiansen and chater 2015"):
  with members:
    - "crossings as a side effect of dependency lengths"
    - "compression and the origins of zipf s law of abbreviation"
    - "reply to the commentary be careful when assuming the obvious by p alday"
    - "the risks of mixing dependency lengths from sequences of different length"
    - "a stronger null hypothesis for crossing dependencies"
    - "the optimality of attaching unlinked labels to unlinked meanings"
    - "the placement of the head that minimizes online memory a complex systems approach"
    - "why sov might be initially preferred and then lost or recovered a theoretical framework"

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)