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: "split correctness in information extraction"
  Abstract: Programs for extracting structured information from text, namely information extractors, often operate separately on document segments obtained from a generic splitting operation such as sentences, paragraphs, k-grams, HTTP requests, and so on. An automated detection of this behavior of extractors, which we refer to as split-correctness, would allow text analysis systems to devise query plans with parallel evaluation on segments for accelerating the processing of large documents. Other applications include the incremental evaluation on dynamic content, where re-evaluation of information extractors can be restricted to revised segments, and debugging, where developers of information extractors are informed about potential boundary crossing of different semantic components. #R##N#We propose a new formal framework for split-correctness within the formalism of document spanners. Our preliminary analysis studies the complexity of split-correctness over regular spanners. We also discuss different variants of split-correctness, for instance, in the presence of black-box extractors with so-called split constraints.

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"
    - "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:
    - "complexity bounds for relational algebra over document spanners"
    - "constant delay enumeration for nondeterministic document spanners"
    - "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 theory of concatenation over finite models"):
  with members:
    - "dynamic complexity of document spanners"
    - "matching patterns with variables"
    - "weight annotation in information extraction"
    - "constant delay enumeration for nondeterministic document spanners"
    - "deterministic regular expressions with back references"
    - "constant delay algorithms for regular document spanners"
    - "the hardness of solving simple word equations"
    - "decidability complexity and expressiveness of first order logic over the subword ordering"

Connected through hyperedge HE-4 (induced by source paper "conjunctive regular path queries with string variables"):
  with members:
    - "boundedness of conjunctive regular path queries"
    - "a trichotomy for regular trail queries"
    - "deterministic regular expressions with back references"
    - "an analytical study of large sparql query logs"
    - "joining extractions of regular expressions"
    - "foundations of modern query languages for graph databases"

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)