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: "document spanners for extracting incomplete information expressiveness and complexity"
  Abstract: Rule-based information extraction has lately received a fair amount of attention from the database community, with several languages appearing in the last few years. Although information extraction systems are intended to deal with semistructured data, all language proposals introduced so far are designed to output relations, thus making them incapable of handling incomplete information. To remedy the situation, we propose to extend information extraction languages with the ability to use mappings, thus allowing us to work with documents which have missing or optional parts. Using this approach, we simplify the semantics of regex formulas and extraction rules, two previously defined methods for extracting information, extend them with the ability to handle incomplete data, and study how they compare in terms of expressive power. We also study computational properties of these languages, focusing on the query enumeration problem, as well as satisfiability and containment.

Connected through hyperedge HE-1 (induced by source paper "grammars for document spanenrs"):
  with members:
    - "complexity bounds for relational algebra over document spanners"
    - "weight annotation in information extraction"
    - "finite models and the theory of concatenation"
    - "constant delay enumeration for nondeterministic document spanners"
    - "split correctness in information extraction"
    - "constant delay algorithms for regular document spanners"
    - "joining extractions of regular expressions"
    - "recursive programs for document spanners"

Connected through hyperedge HE-2 (induced by source paper "dynamic complexity of document spanners"):
  with members:
    - "complexity bounds for relational algebra over document spanners"
    - "constant delay enumeration for nondeterministic document spanners"
    - "split correctness in information extraction"
    - "constant delay algorithms for regular document spanners"
    - "dynamic conjunctive queries"
    - "recursive programs for document spanners"
    - "dynamic graph queries"

Connected through hyperedge HE-3 (induced by source paper "weight annotation in information extraction"):
  with members:
    - "efficient logspace classes for enumeration counting and uniform generation"
    - "complexity bounds for relational algebra over document spanners"
    - "representing formal languages a comparison between finite automata and recurrent neural networks"
    - "constant delay enumeration for nondeterministic document spanners"
    - "constant delay algorithms for regular document spanners"
    - "snorkel rapid training data creation with weak supervision"
    - "extracting automata from recurrent neural networks using queries and counterexamples"
    - "joining extractions of regular expressions"

Connected through hyperedge HE-4 (induced by source paper "complexity bounds for relational algebra over document spanners"):
  with members:
    - "rational recurrences"
    - "constant delay enumeration for nondeterministic document spanners"
    - "constant delay algorithms for regular document spanners"
    - "extracting automata from recurrent neural networks using queries and counterexamples"
    - "enumeration complexity of conjunctive queries with functional dependencies"
    - "joining extractions of regular expressions"
    - "recursive programs for document spanners"
    - "semantics and complexity of sparql"

Connected through hyperedge HE-5 (induced by source paper "efficient logspace classes for enumeration counting and uniform generation"):
  with members:
    - "connecting knowledge compilation classes and width parameters"
    - "constant delay enumeration for nondeterministic document spanners"
    - "descriptive complexity for counting complexity classes"
    - "constant delay algorithms for regular document spanners"
    - "a circuit based approach to efficient enumeration"
    - "joining extractions of regular expressions"
    - "foundations of modern query languages for graph databases"

Connected through hyperedge HE-6 (induced by source paper "constant delay enumeration for nondeterministic document spanners"):
  with members:
    - "enumeration on trees with tractable combined complexity and efficient updates"
    - "enumeration on trees under relabelings"
    - "constant delay algorithms for regular document spanners"
    - "answering fo mod queries under updates on bounded degree databases"
    - "a circuit based approach to efficient enumeration"
    - "answering conjunctive queries under updates"
    - "joining extractions of regular expressions"
    - "answering ucqs under updates and in the presence of integrity constraints"

Connected through hyperedge HE-7 (induced by source paper "split correctness in information extraction"):
  with members:
    - "constant delay algorithms for regular document spanners"
    - "joining extractions of regular expressions"
    - "neural architectures for named entity recognition"
    - "incremental knowledge base construction using deepdive"
    - "named entity recognition with bidirectional lstm cnns"
    - "parallel correctness and transferability for conjunctive queries"
    - "distributed xml design"
    - "a sentimental education sentiment analysis using subjectivity summarization based on minimum cuts"

Connected through hyperedge HE-8 (induced by source paper "constant delay algorithms for regular document spanners"):
  with members:
    - "joining extractions of regular expressions"

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)