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 "chinese pinyin aided ime input what you have not keystroked yet"):
  Abstract: Chinese pinyin input method engine (IME) converts pinyin into character so that Chinese characters can be conveniently inputted into computer through common keyboard. IMEs work relying on its core component, pinyin-to-character conversion (P2C). Usually Chinese IMEs simply predict a list of character sequences for user choice only according to user pinyin input at each turn. However, Chinese inputting is a multi-turn online procedure, which can be supposed to be exploited for further user experience promoting. This paper thus for the first time introduces a sequence-to-sequence model with gated-attention mechanism for the core task in IMEs. The proposed neural P2C model is learned by encoding previous input utterance as extra context to enable our IME capable of predicting character sequence with incomplete pinyin input. Our model is evaluated in different benchmark datasets showing great user experience improvement compared to traditional models, which demonstrates the first engineering practice of building Chinese aided IME.

Includes members:
  Member "finding better subword segmentation for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "lattice based transformer encoder for neural machine translation")
  Member "deep enhanced representation for implicit discourse relation recognition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "unsupervised adversarial domain adaptation for implicit discourse relation classification")
  Member "subword augmented embedding for cloze reading comprehension":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sg net syntax guided machine reading comprehension")
  Member "one shot learning for question answering in gaokao history challenge":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sg net syntax guided machine reading comprehension")
  Member "automatic article commenting the task and dataset":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "clickbait sensational headline generation with auto tuned reinforcement learning")
  Member "modeling multi turn conversation with deep utterance aggregation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sequential neural networks for noetic end to end response selection")
  Member "neural machine translation with extended context":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "multilingual denoising pre training for neural machine translation")
  Member "tracing a loose wordhood for chinese input method engine":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a smart sliding chinese pinyin input method editor on touchscreen")

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.AI(Artificial Intelligence)