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: "vietnamese named entity recognition using token regular expressions and bidirectional inference"
  Abstract: This paper describes an efficient approach to improve the accuracy of a named entity recognition system for Vietnamese. The approach combines regular expressions over tokens and a bidirectional inference method in a sequence labelling model. The proposed method achieves an overall $F_1$ score of 89.66% on a test set of an evaluation campaign, organized in late 2016 by the Vietnamese Language and Speech Processing (VLSP) community.

Connected through hyperedge HE-1 (induced by source paper "on the vietnamese name entity recognition a deep learning method approach"):
  with members:
    - "neural chinese named entity recognition via cnn lstm crf and joint training with word segmentation"
    - "a feature rich vietnamese named entity recognition model"
    - "deep contextualized word representations"
    - "a feature based model for nested named entity recognition at vlsp 2018 ner evaluation campaign"
    - "semi supervised sequence modeling with cross view training"
    - "attentive neural network for named entity recognition in vietnamese"
    - "application of a hybrid bi lstm crf model to the task of russian named entity recognition"
    - "nnvlp a neural network based vietnamese language processing toolkit"

Connected through hyperedge HE-2 (induced by source paper "error analysis for vietnamese named entity recognition on deep neural network models"):
  with members:
    - "neuroner an easy to use program for named entity recognition based on neural networks"
    - "end to end recurrent neural network models for vietnamese named entity recognition word level vs character level"
    - "end to end sequence labeling via bi directional lstm cnns crf"
    - "enriching word vectors with subword information"
    - "neural architectures for named entity recognition"
    - "bidirectional lstm crf models for sequence tagging"
    - "named entity recognition with bidirectional lstm cnns"

Connected through hyperedge HE-3 (induced by source paper "neural sequence labeling for vietnamese pos tagging and ner"):
  with members:
    - "a feature rich vietnamese named entity recognition model"
    - "the importance of automatic syntactic features in vietnamese named entity recognition"
    - "nnvlp a neural network based vietnamese language processing toolkit"
    - "neural architectures for named entity recognition"
    - "bidirectional lstm crf models for sequence tagging"
    - "delving deep into rectifiers surpassing human level performance on imagenet classification"
    - "adam a method for stochastic optimization"
    - "lexicon infused phrase embeddings for named entity resolution"

Connected through hyperedge HE-4 (induced by source paper "a feature rich vietnamese named entity recognition model"):
  with members:
    - "a fast and accurate vietnamese word segmenter"
    - "the importance of automatic syntactic features in vietnamese named entity recognition"
    - "from word segmentation to pos tagging for vietnamese"
    - "nnvlp a neural network based vietnamese language processing toolkit"
    - "named entity recognition with bidirectional lstm cnns"
    - "introduction to the conll 2003 shared task language independent named entity recognition"
    - "introduction to the conll 2002 shared task language independent named entity recognition"

Connected through hyperedge HE-5 (induced by source paper "a factoid question answering system for vietnamese"):
  with members:
    - "building a semantic role labelling system for vietnamese"
    - "ripple down rules for question answering"
    - "nnvlp a neural network based vietnamese language processing toolkit"
    - "open question answering with weakly supervised embedding models"
    - "question answering with subgraph embeddings"

Connected through hyperedge HE-6 (induced by source paper "end to end recurrent neural network models for vietnamese named entity recognition word level vs character level"):
  with members:
    - "end to end sequence labeling via bi directional lstm cnns crf"
    - "neural architectures for named entity recognition"
    - "bidirectional lstm crf models for sequence tagging"
    - "named entity recognition with bidirectional lstm cnns"
    - "boosting named entity recognition with neural character embeddings"
    - "speech recognition with deep recurrent neural networks"
    - "on the difficulty of training recurrent neural networks"
    - "natural language processing almost from scratch"

Connected through hyperedge HE-7 (induced by source paper "the importance of automatic syntactic features in vietnamese named entity recognition"):
  with members:
    - "end to end recurrent neural network models for vietnamese named entity recognition word level vs character level"
    - "neural architectures for named entity recognition"
    - "bidirectional lstm crf models for sequence tagging"
    - "named entity recognition with bidirectional lstm cnns"
    - "speech recognition with deep recurrent neural networks"
    - "natural language processing almost from scratch"

Connected through hyperedge HE-8 (induced by source paper "an empirical study of discriminative sequence labeling models for vietnamese text processing"):
  with members:
    - "end to end recurrent neural network models for vietnamese named entity recognition word level vs character level"
    - "end to end sequence labeling via bi directional lstm cnns crf"
    - "speech recognition with deep recurrent neural networks"
    - "efficient estimation of word representations in vector space"
    - "distributed representations of words and phrases and their compositionality"

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)