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 "conjunctive queries on probabilistic graphs combined complexity"):
  Abstract: Query evaluation over probabilistic databases is known to be intractable in many cases, even in data complexity, i.e., when the query is fixed. Although some restrictions of the queries [19] and instances [4] have been proposed to lower the complexity, these known tractable cases usually do not apply to combined complexity, i.e., when the query is not fixed. This leaves open the question of which query and instance languages ensure the tractability of probabilistic query evaluation in combined complexity. #R##N#This paper proposes the first general study of the combined complexity of conjunctive query evaluation on probabilistic instances over binary signatures, which we can alternatively phrase as a probabilistic version of the graph homomorphism problem, or of a constraint satisfaction problem (CSP) variant. We study the complexity of this problem depending on whether instances and queries can use features such as edge labels, disconnectedness, branching, and edges in both directions. We show that the complexity landscape is surprisingly rich, using a variety of technical tools: automata-based compilation to d-DNNF lineages as in [4], \b{eta}-acyclic lineages using [10], the X-property for tractable CSP from [24], graded DAGs [27] and various coding techniques for hardness proofs.

Includes members:
  Member "tractable lineages on treelike instances limits and extensions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a dichotomy for homomorphism closed queries on probabilistic graphs")
  Member "combined tractability of query evaluation via tree automata and cycluits extended version":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "evaluating datalog via tree automata and cycluits")
  Member "provenance circuits for trees and treelike instances extended version":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "tractable lineages on treelike instances limits and extensions")
  Member "complexity of counting subgraphs only the boundedness of the vertex cover number counts":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "tight bounds for planar strongly connected steiner subgraph with fixed number of terminals and extensions")
  Member "understanding model counting for beta acyclic cnf formulas":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "approximate counting csp seen from the other side")
  Member "symmetric weighted first order model counting":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "abstracting probabilistic models a logical perspective")
  Member "conjunctive queries over trees":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "json data model query languages and schema specification")

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)