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 "open domain event extraction and embedding for natural gas market prediction"):
  Abstract: We propose an approach to predict the natural gas price in several days using historical price data and events extracted from news headlines. Most previous methods treats price as an extrapolatable time series, those analyze the relation between prices and news either trim their price data correspondingly to a public news dataset, manually annotate headlines or use off-the-shelf tools. In comparison to off-the-shelf tools, our event extraction method detects not only the occurrence of phenomena but also the changes in attribution and characteristics from public sources. Instead of using sentence embedding as a feature, we use every word of the extracted events, encode and organize them before feeding to the learning models. Empirical results show favorable results, in terms of prediction performance, money saved and scalability.

Includes members:
  Member "forecasting economics and financial time series arima vs lstm":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "financial time series forecasting with deep learning a systematic literature review 2005 2019")
  Member "cevo comprehensive event ontology enhancing cognitive annotation":
    also connected through other hyperedges:
      (none)
  Member "temporal attention augmented bilinear network for financial time series data analysis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "data normalization for bilinear structures in high frequency financial time series")
  Member "a deeper look into sarcastic tweets using deep convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "modeling sentiment dependencies with graph convolutional networks for aspect level sentiment classification")
  Member "insight 1 at semeval 2016 task 5 deep learning for multilingual aspect based sentiment analysis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a novel aspect guided deep transition model for aspect based sentiment analysis")
  Member "leverage financial news to predict stock price movements using word embeddings and deep neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "unsupervised extraction of market moving events with neural attention")
  Member "modelling visualising and summarising documents with a single convolutional neural network":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the compositionality of neural networks integrating symbolism and connectionism")

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)