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: "scake semantic connectivity aware keyword extraction"
  Abstract: Abstract   Keyword Extraction is an important task in several text analysis endeavours. In this paper, we present a critical discussion of the issues and challenges in graph-based keyword extraction methods, along with comprehensive empirical analysis. We propose a parameterless method for constructing graph of text that captures the contextual relation between words. A novel word scoring method is also proposed based on the connection between concepts. We demonstrate that both proposals are individually superior to those followed by the sate-of-the-art graph-based keyword extraction algorithms. Combination of the proposed graph construction and scoring methods leads to a novel, parameterless keyword extraction method (sCAKE) based on semantic connectivity of words in the document.  Motivated by limited availability of NLP tools for several languages, we also design and present a language-agnostic keyword extraction (LAKE) method. We eliminate the need of NLP tools by using a statistical filter to identify candidate keywords before constructing the graph. We show that the resulting method is a competent solution for extracting keywords from documents of languages lacking sophisticated NLP support.

Connected through hyperedge HE-1 (induced by source paper "complex network based supervised keyword extractor"):
  with members:
    - "unsupervised keyphrase extraction with multipartite graphs"
    - "xgboost a scalable tree boosting system"
    - "supervised topical key phrase extraction of news stories using crowdsourcing light filtering and co reference normalization"
    - "statistical keyword detection in literary corpora"
    - "smote synthetic minority over sampling technique"
    - "kea practical automatic keyphrase extraction"
    - "learning to extract keyphrases from text"

Connected through hyperedge HE-2 (induced by source paper "a spark ml driven preprocessing approach for deep learning based scholarly data applications"):
  with members:
    - "pabed a tool for big education data analysis"
    - "deep keyphrase generation"
    - "accurate large minibatch sgd training imagenet in 1 hour"
    - "modelling sentence pairs with tree structured attentive encoder"
    - "recurrent neural network for text classification with multi task learning"
    - "sequence to sequence rnns for text summarization"
    - "mllib machine learning in apache spark"
    - "improved semantic representations from tree structured long short term memory networks"

Connected through hyperedge HE-3 (induced by source paper "semi automatic system for title construction"):
  with members:
    - "dtatg an automatic title generator based on dependency trees"

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.IR(Information Retrieval)