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 "tractable lineages on treelike instances limits and extensions"):
  Abstract: Query evaluation on probabilistic databases is generally intractable (#P-hard). Existing dichotomy results have identified which queries are tractable (or safe), and connected them to tractable lineages. In our previous work, using different tools, we showed that query evaluation is linear-time on probabilistic databases for arbitrary monadic second-order queries, if we bound the treewidth of the instance.   In this paper, we study limitations and extensions of this result. First, for probabilistic query evaluation, we show that MSO tractability cannot extend beyond bounded treewidth: there are even FO queries that are hard on any efficiently constructible unbounded-treewidth class of graphs. This dichotomy relies on recent polynomial bounds on the extraction of planar graphs as minors, and implies lower bounds in non-probabilistic settings, for query evaluation and match counting in subinstance-closed families. Second, we show how to explain our tractability result in terms of lineage: the lineage of MSO queries on bounded-treewidth instances can be represented as bounded-treewidth circuits, polynomial-size OBDDs, and linear-size d-DNNFs. By contrast, we can strengthen the previous dichotomy to lineages, and show that there are even UCQs with disequalities that have superpolynomial OBDDs on all unbounded-treewidth graph classes; we give a characterization of such queries. Last, we show how bounded-treewidth tractability explains the tractability of the inversion-free safe queries: we can rewrite their input instances to have bounded-treewidth.

Includes members:
  Member "provenance circuits for trees and treelike instances extended version":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "conjunctive queries on probabilistic graphs combined complexity")
  Member "approximate lifted inference with probabilistic databases":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "generalized lineage aware temporal windows supporting outer and anti joins in temporal probabilistic databases")
  Member "polynomial bounds for the grid minor theorem":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hitting topological minors is fpt")
  Member "complexity of inference in graphical models":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "worst case polynomial time exact map inference on discrete models with global dependencies")
  Member "lower bounds for the complexity of monadic second order logic":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "model checking on ordered structures")
  Member "are there any good digraph width measures":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "width parameterizations for knot free vertex deletion on digraphs")
  Member "algorithmic meta theorems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "nowhere dense graph classes and algorithmic applications a tutorial at highlights of logic games and automata 2019")
  Member "tractable hypergraph properties for constraint satisfaction and conjunctive queries":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "complexity analysis of general and fractional hypertree decompositions")

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)