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 "modeling harmony with skip grams"):
  Abstract: String-based (or viewpoint) models of tonal harmony often struggle with data sparsity in pattern discovery and prediction tasks, particularly when modeling composite events like triads and seventh chords, since the number of distinct n-note combinations in polyphonic textures is potentially enormous. To address this problem, this study examines the efficacy of skip-grams in music research, an alternative viewpoint method developed in corpus linguistics and natural language processing that includes sub-sequences of n events (or n-grams) in a frequency distribution if their constituent members occur within a certain number of skips. #R##N#Using a corpus consisting of four datasets of Western classical music in symbolic form, we found that including skip-grams reduces data sparsity in n-gram distributions by (1) minimizing the proportion of n-grams with negligible counts, and (2) increasing the coverage of contiguous n-grams in a test corpus. What is more, skip-grams significantly outperformed contiguous n-grams in discovering conventional closing progressions (called cadences).

Includes members:
  Member "zipf s law holds for phrases not words":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "neutral evolution and turnover over centuries of english word popularity")
  Member "a bit of progress in language modeling":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "scaling laws for neural language models")

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.IR(Information Retrieval)