human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "column2vec structural understanding via distributed representations of database schemas"):
  Abstract: We present Column2Vec, a distributed representation of database columns based on column metadata. Our distributed representation has several applications. Using known names for groups of columns (i.e., a table name), we train a model to generate an appropriate name for columns in an unnamed table. We demonstrate the viability of our approach using schema information collected from open source applications on GitHub.

Includes members:
  Member "data curation with deep learning vision towards self driving data curation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "slide in defense of smart algorithms over hardware acceleration for large scale deep learning systems")
  Member "deep contextualized word representations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "bert pre training of deep bidirectional transformers for language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "deeper deep entity resolution":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "autoblock a hands off blocking framework for entity matching")
  Member "vector embedding of wikipedia concepts and entities":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "generating timelines by modeling semantic change")
  Member "graph2vec learning distributed representations of graphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "few shot learning on graphs via super classes based on graph spectral measures")
  Member "generative topic embedding a continuous representation of documents extended version with proofs":
    also connected through other hyperedges:
      (none)
  Member "mixing dirichlet topic models and word embeddings to make lda2vec":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "improving document classification with multi sense embeddings")

Question: Please tell me which class the source paper 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.DB(Databases)