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 "music sequence prediction with mixture hidden markov models"):
  Abstract: Recommendation systems that automatically generate personalized music playlists for users have attracted tremendous attention in recent years. Nowadays, most music recommendation systems rely on item-based or user-based collaborative filtering or content-based approaches. In this paper, we propose a novel mixture hidden Markov model (HMM) for music play sequence prediction. We compare the mixture model with state-of-the-art methods and evaluate the predictions quantitatively and qualitatively on a large-scale real-world dataset in a Kaggle competition. Results show that our model significantly outperforms traditional methods as well as other competitors. We conclude by envisioning a next-generation music recommendation system that integrates our model with recent advances in deep learning, computer vision, and speech techniques, and has promising potential in both academia and industry.

Includes members:
  Member "understanding beauty via deep facial features":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "anonymousnet natural face de identification with measurable privacy")
  Member "anonymousnet natural face de identification with measurable privacy":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fawkes protecting personal privacy against unauthorized deep learning models")
  Member "component attention guided face super resolution network cagface":
    also connected through other hyperedges:
      (none)
  Member "multiclass information flow propagation control under vehicle to vehicle communication environments":
    also connected through other hyperedges:
      (none)
  Member "cooperative adaptive cruise control for connected autonomous vehicles by factoring communication related constraints":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "semi supervised text regression with conditional generative adversarial networks")
  Member "youtube av 50k an annotated corpus for comments in autonomous vehicles":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cooperative adaptive cruise control for connected autonomous vehicles by factoring communication related constraints")
  Member "cooperative adaptive cruise control for a platoon of connected and autonomous vehicles considering dynamic information flow topology":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "cooperative adaptive cruise control for connected autonomous vehicles by factoring communication related constraints")
  Member "towards reading hidden emotions a comparative study of spontaneous micro expression spotting and recognition methods":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "spatiotemporal recurrent convolutional networks for recognizing spontaneous micro expressions")

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)