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: "elixa a modular and flexible absa platform"
  Abstract: This paper presents a supervised Aspect Based Sentiment Analysis (ABSA) system. Our aim is to develop a modular platform which allows to easily conduct experiments by replacing the modules or adding new features. We obtain the best result in the Opinion Target Extraction (OTE) task (slot 2) using an off-the-shelf sequence labeler. The target polarity classification (slot 3) is addressed by means of a multiclass SVM algorithm which includes lexical based features such as the polarity values obtained from domain and open polarity lexicons. The system obtains accuracies of 0.70 and 0.73 for the restaurant and laptop domain respectively, and performs second best in the out-of-domain hotel, achieving an accuracy of 0.80.

Connected through hyperedge HE-1 (induced by source paper "pod positional dependency based word embedding for aspect term extraction"):
  with members:
    - "language models with transformers"
    - "double embeddings and cnn based sequence labeling for aspect extraction"
    - "self attention with relative position representations"
    - "deep contextualized word representations"
    - "aspect term extraction with history attention and selective transformation"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "attention is all you need"
    - "recursive neural conditional random fields for aspect based sentiment analysis"

Connected through hyperedge HE-2 (induced by source paper "neural aspect and opinion term extraction with mined rules as weak supervision"):
  with members:
    - "double embeddings and cnn based sequence labeling for aspect extraction"
    - "aspect term extraction with history attention and selective transformation"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "transfer learning for sequence tagging with hierarchical recurrent networks"
    - "recursive neural conditional random fields for aspect based sentiment analysis"
    - "unsupervised word and dependency path embeddings for aspect term extraction"
    - "ups and downs modeling the visual evolution of fashion trends with one class collaborative filtering"
    - "bidirectional lstm crf models for sequence tagging"

Connected through hyperedge HE-3 (induced by source paper "language independent sequence labelling for opinion target extraction"):
  with members:
    - "aspect based relational sentiment analysis using a stacked neural network architecture"
    - "robust multilingual named entity recognition with shallow semi supervised features"
    - "unsupervised word and dependency path embeddings for aspect term extraction"
    - "distributed representations of words and phrases and their compositionality"
    - "thumbs up sentiment classification using machine learning techniques"
    - "introduction to the conll 2002 shared task language independent named entity recognition"

Connected through hyperedge HE-4 (induced by source paper "zero shot cross lingual opinion target extraction"):
  with members:
    - "offline bilingual word vectors orthogonal transformations and the inverted softmax"
    - "enriching word vectors with subword information"
    - "adam a method for stochastic optimization"
    - "representing text chunks"

Connected through hyperedge HE-5 (induced by source paper "real time monitoring of social media and digital press"):
  with members:
    - "semeval 2016 task 4 sentiment analysis in twitter"
    - "semeval 2017 task 4 sentiment analysis in twitter"
    - "bb_twtr at semeval 2017 task 4 twitter sentiment analysis with cnns and lstms"
    - "leveraging large amounts of weakly supervised data for multi language sentiment classification"
    - "towards real time country level location classification of worldwide tweets"
    - "semi supervised sequence learning"
    - "nrc canada building the state of the art in sentiment analysis of tweets"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-6 (induced by source paper "aspect based sentiment analysis using a two step neural network architecture"):
  with members:
    - "inferring networks of substitutable and complementary products"
    - "image based recommendations on styles and substitutes"
    - "classifying relations by ranking with convolutional neural networks"
    - "adam a method for stochastic optimization"
    - "distributed representations of sentences and documents"
    - "retrofitting word vectors to semantic lexicons"
    - "empirical evaluation of gated recurrent neural networks on sequence modeling"
    - "learning phrase representations using rnn encoder decoder for statistical machine translation"

Connected through hyperedge HE-7 (induced by source paper "unsupervised word and dependency path embeddings for aspect term extraction"):
  with members:
    - "dependency recurrent neural language models for sentence completion"
    - "modeling relation paths for representation learning of knowledge bases"
    - "unsupervised cross domain word representation learning"
    - "a dependency based neural network for relation classification"
    - "compositional vector space models for knowledge base completion"
    - "efficient estimation of word representations in vector space"
    - "distributed representations of words and phrases and their compositionality"
    - "representation learning a review and new perspectives"

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)