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 "constant delay enumeration for nondeterministic document spanners"):
  Abstract: We consider the information extraction approach known as document spanners, and study the problem of efficiently computing the results of the extraction from an input document, where the extraction task is described as a sequential variable-set automaton (VA). We pose this problem in the setting of enumeration algorithms, where we can first run a preprocessing phase and must then produce the results with a small delay between any two consecutive results. Our goal is to have an algorithm which is tractable in combined complexity, i.e., in the input document and in the VA; while ensuring the best possible data complexity bounds in the input document, in particular constant delay in the document. Several recent works at PODS'18 proposed such algorithms but with linear delay in the document or with an exponential dependency in the (generally nondeterministic) input VA. Florenzano et al. suggest that our desired runtime guarantees cannot be met for general sequential VAs. We refute this and show that, given a nondeterministic sequential VA and an input document, we can enumerate the mappings of the VA on the document with the following bounds: the preprocessing is linear in the document size and polynomial in the size of the VA, and the delay is independent of the document and polynomial in the size of the VA. The resulting algorithm thus achieves tractability in combined complexity and the best possible data complexity bounds. Moreover, it is rather easy to describe, in particular for the restricted case of so-called extended VAs.

Includes members:
  Member "enumeration on trees with tractable combined complexity and efficient updates":
    also connected through other hyperedges:
      (none)
  Member "enumeration on trees under relabelings":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "constant delay enumeration with fpt preprocessing for conjunctive queries of bounded submodular width")
  Member "constant delay algorithms for regular document spanners":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "grammars for document spanenrs")
  Member "answering fo mod queries under updates on bounded degree databases":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "constant delay enumeration with fpt preprocessing for conjunctive queries of bounded submodular width")
  Member "a circuit based approach to efficient enumeration":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "efficient logspace classes for enumeration counting and uniform generation")
  Member "answering conjunctive queries under updates":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "constant delay enumeration with fpt preprocessing for conjunctive queries of bounded submodular width")
  Member "document spanners for extracting incomplete information expressiveness and complexity":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "grammars for document spanenrs")
  Member "joining extractions of regular expressions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "grammars for document spanenrs")

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)