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: "complexity bounds for relational algebra over document spanners"
  Abstract: We investigate the complexity of evaluating queries in Relational Algebra (RA) over the relations extracted by regex formulas (i.e., regular expressions with capture variables) over text documents. Such queries, also known as the regular document spanners, were shown to have an evaluation with polynomial delay for every positive RA expression (i.e., consisting of only natural joins, projections and unions); here, the RA expression is fixed and the input consists of both the regex formulas and the document. In this work, we explore the implication of two fundamental generalizations. The first is adopting the "schemaless" semantics for spanners, as proposed and studied by Maturana et al. The second is going beyond the positive RA to allowing the difference operator. We show that each of the two generalizations introduces computational hardness: it is intractable to compute the natural join of two regex formulas under the schemaless semantics, and the difference between two regex formulas under both the ordinary and schemaless semantics. Nevertheless, we propose and analyze syntactic constraints, on the RA expression and the regex formulas at hand, such that the expressive power is fully preserved and, yet, evaluation can be done with polynomial delay. Unlike the previous work on RA over regex formulas, our technique is not (and provably cannot be) based on the static compilation of regex formulas, but rather on an ad-hoc compilation into an automaton that incorporates both the query and the document. This approach also allows us to include black-box extractors in the RA expression.

Connected through hyperedge HE-1 (induced by source paper "grammars for document spanenrs"):
  with members:
    - "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"
    - "document spanners for extracting incomplete information expressiveness and complexity"
    - "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:
    - "constant delay enumeration for nondeterministic document spanners"
    - "split correctness in information extraction"
    - "constant delay algorithms for regular document spanners"
    - "dynamic conjunctive queries"
    - "document spanners for extracting incomplete information expressiveness and complexity"
    - "recursive programs for document spanners"
    - "dynamic graph queries"

Connected through hyperedge HE-3 (induced by source paper "the complexity of aggregates over extractions by regular expressions"):
  with members:
    - "constant delay enumeration for nondeterministic document spanners"
    - "constant delay algorithms for regular document spanners"
    - "joining extractions of regular expressions"

Connected through hyperedge HE-4 (induced by source paper "weight annotation in information extraction"):
  with members:
    - "efficient logspace classes for enumeration counting and uniform generation"
    - "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"
    - "document spanners for extracting incomplete information expressiveness and complexity"
    - "snorkel rapid training data creation with weak supervision"
    - "extracting automata from recurrent neural networks using queries and counterexamples"
    - "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)