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: "lower bounds for exact model counting and applications in probabilistic databases"
  Abstract: The best current methods for exactly computing the number of satisfying assignments, or the satisfying probability, of Boolean formulas can be seen, either directly or indirectly, as building 'decision-DNNF' (decision decomposable negation normal form) representations of the input Boolean formulas. Decision-DNNFs are a special case of 'd-DNNF's where 'd' stands for 'deterministic'. We show that any decision-DNNF can be converted into an equivalent 'FBDD' (free binary decision diagram) -- also known as a 'read-once branching program' (ROBP or 1-BP) -- with only a quasipolynomial increase in representation size in general, and with only a polynomial increase in size in the special case of monotone k-DNF formulas. Leveraging known exponential lower bounds for FBDDs, we then obtain similar exponential lower bounds for decision-DNNFs which provide lower bounds for the recent algorithms. We also separate the power of decision-DNNFs from d-DNNFs and a generalization of decision-DNNFs known as AND-FBDDs. Finally we show how these imply exponential lower bounds for natural problems associated with probabilistic databases.

Connected through hyperedge HE-1 (induced by source paper "on the relation between structured d dnnfs and sdds"):
  with members:
    - "smoothing structured decomposable circuits"
    - "on the relative succinctness of sentential decision diagrams"
    - "circuit treewidth sentential decision and query compilation"
    - "sdds are exponentially more succinct than obdds"
    - "new limits for knowledge compilation and applications to exact model counting"
    - "on compiling structured cnfs to obdds"
    - "a knowledge compilation map"

Connected through hyperedge HE-2 (induced by source paper "knowledge compilation languages as proof systems"):
  with members:
    - "pebble games proof complexity and time space trade offs"
    - "a knowledge compilation map"

Connected through hyperedge HE-3 (induced by source paper "connecting knowledge compilation classes and width parameters"):
  with members:
    - "towards deterministic decomposable circuits for safe queries"
    - "on the relative succinctness of sentential decision diagrams"
    - "connecting width and structure in knowledge compilation"
    - "understanding the complexity of sat using knowledge compilation"
    - "a circuit based approach to efficient enumeration"
    - "non fpt lower bounds for structural restrictions of decision dnnf"
    - "circuit treewidth sentential decision and query compilation"
    - "tractable lineages on treelike instances limits and extensions"

Connected through hyperedge HE-4 (induced by source paper "on the relative succinctness of sentential decision diagrams"):
  with members:
    - "a superpolynomial lower bound for the size of non deterministic complement of an unambiguous automaton"
    - "non fpt lower bounds for structural restrictions of decision dnnf"
    - "circuit treewidth sentential decision and query compilation"
    - "sdds are exponentially more succinct than obdds"
    - "new limits for knowledge compilation and applications to exact model counting"
    - "on oblivious branching programs with bounded repetition that cannot efficiently compute cnfs of bounded treewidth"
    - "on the read once property of branching programs and cnfs of bounded treewidth"
    - "the language of search"

Connected through hyperedge HE-5 (induced by source paper "understanding the complexity of sat using knowledge compilation"):
  with members:
    - "new limits for knowledge compilation and applications to exact model counting"
    - "hypergraph acyclicity and propositional model counting"
    - "solving maxsat and sat on structured cnf formulas"
    - "understanding model counting for beta acyclic cnf formulas"
    - "no small nondeterministic read once branching programs for cnfs of bounded treewidth"
    - "model counting for formulas of bounded clique width"
    - "on obdds for cnfs of bounded treewidth"
    - "satisfiability of acyclic and almost acyclic cnf formulas"

Connected through hyperedge HE-6 (induced by source paper "non fpt lower bounds for structural restrictions of decision dnnf"):
  with members:
    - "understanding the complexity of sat using knowledge compilation"
    - "hypergraph acyclicity and propositional model counting"
    - "solving maxsat and sat on structured cnf formulas"
    - "understanding model counting for beta acyclic cnf formulas"
    - "no small nondeterministic read once branching programs for cnfs of bounded treewidth"
    - "model counting for formulas of bounded clique width"
    - "on obdds for cnfs of bounded treewidth"

Connected through hyperedge HE-7 (induced by source paper "new limits for knowledge compilation and applications to exact model counting"):
  with members:
    - "on the read once property of branching programs and cnfs of bounded treewidth"
    - "on obdds for cnfs of bounded treewidth"
    - "the language of search"

Connected through hyperedge HE-8 (induced by source paper "expander cnfs have exponential dnnf size"):
  with members:
    - "no small nondeterministic read once branching programs for cnfs of bounded treewidth"
    - "on compiling structured cnfs to obdds"
    - "on the read once property of branching programs and cnfs of bounded treewidth"
    - "on obdds for cnfs of bounded treewidth"
    - "a knowledge compilation map"

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)