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: "learning semantic string transformations from examples"
  Abstract: We address the problem of performing semantic transformations on strings, which may represent a variety of data types (or their combination) such as a column in a relational table, time, date, currency, etc. Unlike syntactic transformations, which are based on regular expressions and which interpret a string as a sequence of characters, semantic transformations additionally require exploiting the semantics of the data type represented by the string, which may be encoded as a database of relational tables. Manually performing such transformations on a large collection of strings is error prone and cumbersome, while programmatic solutions are beyond the skill-set of end-users. We present a programming by example technology that allows end-users to automate such repetitive tasks. We describe an expressive transformation language for semantic manipulation that combines table lookup operations and syntactic manipulations. We then present a synthesis algorithm that can learn all transformations in the language that are consistent with the user-provided set of input-output examples. We have implemented this technology as an add-in for the Microsoft Excel Spreadsheet system and have evaluated it successfully over several benchmarks picked from various Excel help-forums.

Connected through hyperedge HE-1 (induced by source paper "multi modal synthesis of regular expressions"):
  with members:
    - "seq2sql generating structured queries from natural language using reinforcement learning"
    - "nl2bash a corpus and semantic parser for natural language interface to the linux operating system"
    - "program synthesis using abstraction refinement"
    - "program synthesis using conflict driven learning"
    - "synthesis of data completion scripts using finite tree automata"
    - "learning a natural language interface with neural programmer"
    - "neural generation of regular expressions from natural language with minimal domain knowledge"
    - "component based synthesis of table consolidation and transformation tasks from examples"

Connected through hyperedge HE-2 (induced by source paper "presistant learning based assistant for data pre processing"):
  with members:
    - "evaluation of a tree based pipeline optimization tool for automating data science"
    - "xgboost a scalable tree boosting system"
    - "openml networked science in machine learning"
    - "auto weka combined selection and hyperparameter optimization of classification algorithms"

Connected through hyperedge HE-3 (induced by source paper "flashprofile a framework for synthesizing dataprofiles"):
  with members:
    - "synthesizing program input grammars"
    - "the madlib analytics library or mad skills the sql"

Connected through hyperedge HE-4 (induced by source paper "towards a theory of data diff optimal synthesis of succinct data modification scripts"):
  with members:
    - "principles of dataset versioning exploring the recreation storage tradeoff"

Connected through hyperedge HE-5 (induced by source paper "learning with latent language"):
  with members:
    - "grounding language for transfer in deep reinforcement learning"
    - "robustfill neural program learning under noisy i o"
    - "representation learning for grounded spatial reasoning"
    - "prototypical networks for few shot learning"
    - "guiding reinforcement learning exploration using natural language"
    - "rl 2 fast reinforcement learning via slow reinforcement learning"
    - "shapeworld a new test methodology for multimodal language understanding"
    - "model agnostic meta learning for fast adaptation of deep networks"

Connected through hyperedge HE-6 (induced by source paper "unsupervised string transformation learning for entity consolidation"):
  with members:
    - "neural guided deductive search for real time program synthesis from examples"
    - "slimfast guaranteed results for data fusion and source reliability"
    - "incremental knowledge base construction using deepdive"
    - "truth discovery algorithms an experimental evaluation"
    - "pass join a partition based method for similarity joins"

Connected through hyperedge HE-7 (induced by source paper "synthesizing bijective lenses"):
  with members:
    - "reflections on monadic lenses"
    - "component based synthesis of table consolidation and transformation tasks from examples"
    - "program synthesis from polymorphic refinement types"

Connected through hyperedge HE-8 (induced by source paper "webrelate integrating web data with spreadsheets using examples"):
  with members:
    - "robustfill neural program learning under noisy i o"
    - "program synthesis using abstraction refinement"
    - "synthesis of data completion scripts using finite tree automata"

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.DB(Databases)