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: "computational induction of prosodic structure"
  Abstract: The present study has two goals relating to the grammar of prosody, understood as the rhythms and melodies of speech. First, an overview is provided of the computable grammatical and phonetic approaches to prosody analysis which use hypothetico-deductive methods and are based on learned hermeneutic intuitions about language. Second, a proposal is presented for an inductive grounding in the physical signal, in which prosodic structure is inferred using a language-independent method from the low-frequency spectrum of the speech signal. The overview includes a discussion of computational aspects of standard generative and post-generative models, and suggestions for reformulating these to form inductive approaches. Also included is a discussion of linguistic phonetic approaches to analysis of annotations (pairs of speech unit labels with time-stamps) of recorded spoken utterances. The proposal introduces the inductive approach of Rhythm Formant Theory (RFT) and the associated Rhythm Formant Analysis (RFA) method are introduced, with the aim of completing a gap in the linguistic hypothetico-deductive cycle by grounding in a language-independent inductive procedure of speech signal analysis. The validity of the method is demonstrated and applied to rhythm patterns in read-aloud Mandarin Chinese, finding differences from English which are related to lexical and grammatical differences between the languages, as well as individual variation. The overall conclusions are (1) that normative language-to-language phonological or phonetic comparisons of rhythm, for example of Mandarin and English, are too simplistic, in view of diverse language-internal factors due to genre and style differences as well as utterance dynamics, and (2) that language-independent empirical grounding of rhythm in the physical signal is called for.

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)