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 "deep sentiment sentiment analysis using ensemble of cnn and bi lstm models"):
  Abstract: With the popularity of social networks, and e-commerce websites, sentiment analysis has become a more active area of research in the past few years. On a high level, sentiment analysis tries to understand the public opinion about a specific product or topic, or trends from reviews or tweets. Sentiment analysis plays an important role in better understanding customer/user opinion, and also extracting social/political trends. There has been a lot of previous works for sentiment analysis, some based on hand-engineering relevant textual features, and others based on different neural network architectures. In this work, we present a model based on an ensemble of long-short-term-memory (LSTM), and convolutional neural network (CNN), one to capture the temporal information of the data, and the other one to extract the local structure thereof. Through experimental results, we show that using this ensemble model we can outperform both individual models. We are also able to achieve a very high accuracy rate compared to the previous works.

Includes members:
  Member "deep learning for sentiment analysis a survey":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an end to end visual audio attention network for emotion recognition in user generated videos")
  Member "mtbi identification from diffusion mr images using bag of adversarial visual features":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deep emotion facial expression recognition using attentional convolutional network")
  Member "deep learning for hate speech detection in tweets":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ties temporal interaction embeddings for enhancing social media integrity at facebook")
  Member "automatic question answering using a deep similarity neural network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deepiris iris recognition using a deep learning approach")
  Member "mask r cnn":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "relatext exploiting visual relationships for arbitrary shaped scene text detection with graph convolutional networks")
  Member "deep reinforcement learning for dialogue generation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "generative adversarial networks in computer vision a survey and taxonomy")
  Member "ssd single shot multibox detector":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "relatext exploiting visual relationships for arbitrary shaped scene text detection with graph convolutional networks")
  Member "the darpa twitter bot challenge":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "don t feed the troll detecting troll behavior via inverse reinforcement learning")

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)