human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "happydb a corpus of 100 000 crowdsourced happy moments"
  Abstract: The science of happiness is an area of positive psychology concerned with understanding what behaviors make people happy in a sustainable fashion. Recently, there has been interest in developing technologies that help incorporate the findings of the science of happiness into users' daily lives by steering them towards behaviors that increase happiness. With the goal of building technology that can understand how people express their happy moments in text, we crowd-sourced HappyDB, a corpus of 100,000 happy moments that we make publicly available. This paper describes HappyDB and its properties, and outlines several important NLP problems that can be studied with the help of the corpus. We also apply several state-of-the-art analysis techniques to analyze HappyDB. Our results demonstrate the need for deeper NLP techniques to be developed which makes HappyDB an exciting resource for follow-on research.

Connected through hyperedge HE-1 (induced by source paper "multi modal sentiment analysis using super characters method on low power cnn accelerator device"):
  with members:
    - "superchat dialogue generation by transfer learning from vision to language using two dimensional word embedding"
    - "supertml two dimensional word embedding for the precognition on structured tabular data"
    - "supercaptioning image captioning using two dimensional word embedding"
    - "system demo for transfer learning across vision and text using domain specific cnn accelerator for on device nlp applications"
    - "squared english word a method of generating glyph to use super characters for sentiment analysis"
    - "super characters a conversion from sentiment classification to image classification"

Connected through hyperedge HE-2 (induced by source paper "happy together learning and understanding appraisal from natural language"):
  with members:
    - "allennlp a deep semantic natural language processing platform"
    - "deep contextualized word representations"
    - "universal language model fine tuning for text classification"
    - "learned in translation contextualized word vectors"
    - "cached long short term memory neural networks for document level sentiment classification"
    - "recurrent neural network for text classification with multi task learning"
    - "improved semantic representations from tree structured long short term memory networks"
    - "one billion word benchmark for measuring progress in statistical language modeling"

Connected through hyperedge HE-3 (induced by source paper "squared english word a method of generating glyph to use super characters for sentiment analysis"):
  with members:
    - "super characters a conversion from sentiment classification to image classification"
    - "attention is all you need"
    - "which encoding is the best for text classification in chinese english japanese and korean"
    - "xgboost a scalable tree boosting system"
    - "bag of tricks for efficient text classification"
    - "character level convolutional networks for text classification"
    - "neural machine translation by jointly learning to align and translate"

Connected through hyperedge HE-4 (induced by source paper "happiness entailment automating suggestions for well being"):
  with members:
    - "happy together learning and understanding appraisal from natural language"
    - "jo the smart journal"
    - "supervised learning of universal sentence representations from natural language inference data"
    - "a structured self attentive sentence embedding"
    - "a decomposable attention model for natural language inference"
    - "a large annotated corpus for learning natural language inference"

Connected through hyperedge HE-5 (induced by source paper "cruzaffect at affcon 2019 shared task a feature rich approach to characterize happiness"):
  with members:
    - "linguistic reflexes of well being and happiness in echo"
    - "learning lexico functional patterns for first person affect"
    - "xgboost a scalable tree boosting system"
    - "a sensitivity analysis of and practitioners guide to convolutional neural networks for sentence classification"

Connected through hyperedge HE-6 (induced by source paper "jo the smart journal"):
  with members:
    - "voyageur an experiential travel search engine"
    - "subjective databases"

Connected through hyperedge HE-7 (induced by source paper "scalable semantic querying of text"):
  with members:
    - "sling a framework for frame semantic parsing"
    - "efficient indexing and querying over syntactically annotated trees"
    - "natural language processing almost from scratch"
    - "a universal part of speech tagset"

Question: Please tell me which class the center node 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)