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: "term set expansion based nlp architect by intel ai lab"
  Abstract: We present SetExpander, a corpus-based system for expanding a seed set of terms into amore complete set of terms that belong to the same semantic class. SetExpander implements an iterative end-to-end workflow. It enables users to easily select a seed set of terms, expand it, view the expanded set, validate it, re-expand the validated set and store it, thus simplifying the extraction of domain-specific fine-grained semantic classes.SetExpander has been used successfully in real-life use cases including integration into an automated recruitment system and an issues and defects resolution system. A video demo of SetExpander is available at this https URL (some images were blurred for privacy reasons)

Connected through hyperedge HE-1 (induced by source paper "guiding corpus based set expansion by auxiliary sets generation and co expansion"):
  with members:
    - "discriminative topic mining via category name guided text embedding"
    - "analogies explained towards understanding word embeddings"
    - "setexpan corpus based set expansion via context feature selection and rank ensemble"
    - "fuse multi faceted set expansion by coherent clustering of skip grams"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-2 (induced by source paper "multi context term embeddings the use case of corpus based term set expansion"):
  with members:
    - "setexpan corpus based set expansion via context feature selection and rank ensemble"
    - "term set expansion based on multi context term embeddings an end to end workflow"
    - "distributional term set expansion"
    - "a deeper look into dependency based word embeddings"
    - "deep contextualized word representations"
    - "deep sets"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "fasttext zip compressing text classification models"

Connected through hyperedge HE-3 (induced by source paper "fuse multi faceted set expansion by coherent clustering of skip grams"):
  with members:
    - "hardware guided symbiotic training for compact accurate yet execution efficient lstm"
    - "setexpan corpus based set expansion via context feature selection and rank ensemble"
    - "hiexpan task guided taxonomy construction by hierarchical tree expansion"
    - "grow and prune compact fast and accurate lstms"
    - "multilingual models for compositional distributed semantics"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-4 (induced by source paper "course concept expansion in moocs with external knowledge and interactive game"):
  with members:
    - "setexpan corpus based set expansion via context feature selection and rank ensemble"
    - "analogical reasoning on chinese morphological and semantic relations"
    - "xgboost a scalable tree boosting system"
    - "learning phrase representations using rnn encoder decoder for statistical machine translation"

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.AI(Artificial Intelligence)