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 "transfer learning for context aware question matching in information seeking conversations in e commerce"):
  Abstract: Building multi-turn information-seeking conversation systems is an important and challenging research topic. Although several advanced neural text matching models have been proposed for this task, they are generally not efficient for industrial applications. Furthermore, they rely on a large amount of labeled data, which may not be available in real-world applications. To alleviate these problems, we study transfer learning for multi-turn information seeking conversations in this paper. We first propose an efficient and effective multi-turn conversation model based on convolutional neural networks. After that, we extend our model to adapt the knowledge learned from a resource-rich domain to enhance the performance. Finally, we deployed our model in an industrial chatbot called AliMe Assist (this https URL) and observed a significant improvement over the existing online model.

Includes members:
  Member "alime assist an intelligent assistant for creating an innovative e commerce experience":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "iart intent aware response ranking with transformers in information seeking conversation systems")
  Member "response ranking with deep matching networks and external knowledge in information seeking conversation systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "iart intent aware response ranking with transformers in information seeking conversation systems")
  Member "adversarial multi criteria learning for chinese word segmentation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "integrating boundary assembling into a dnn framework for named entity recognition in chinese social media text")
  Member "transfer learning for sequence tagging with hierarchical recurrent networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "zero resource cross domain named entity recognition")
  Member "modelling domain relationships for transfer learning on retrieval based question answering systems in e commerce":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "iart intent aware response ranking with transformers in information seeking conversation systems")
  Member "a persona based neural conversation model":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "non autoregressive neural dialogue generation")
  Member "unsupervised cross domain image generation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "gan compression efficient architectures for interactive conditional gans")
  Member "deep reinforcement learning for dialogue generation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "generative adversarial networks in computer vision a survey and taxonomy")

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.CL(Computation and Language)