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: "circuit treewidth sentential decision and query compilation"
  Abstract: The evaluation of a query over a probabilistic database boils down to computing the probability of a suitable Boolean function, the lineage of the query over the database. The method of query compilation approaches the task in two stages: first, the query lineage is implemented (compiled) in a circuit form where probability computation is tractable; and second, the desired probability is computed over the compiled circuit. A basic theoretical quest in query compilation is that of identifying pertinent classes of queries whose lineages admit compact representations over increasingly succinct, tractable circuit classes. Fostering previous work by Jha and Suciu (2012) and Petke and Razgon (2013), we focus on queries whose lineages admit circuit implementations with small treewidth, and investigate their compilability within tame classes of decision diagrams. In perfect analogy with the characterization of bounded circuit pathwidth by bounded OBDD width, we show that a class of Boolean functions has bounded circuit treewidth if and only if it has bounded SDD width. Sentential decision diagrams (SDDs) are central in knowledge compilation, being essentially as tractable as OBDDs but exponentially more succinct. By incorporating constant width SDDs and polynomial size SDDs, we refine the panorama of query compilation for unions of conjunctive queries with and without inequalities.

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"
    - "sdds are exponentially more succinct than obdds"
    - "new limits for knowledge compilation and applications to exact model counting"
    - "on compiling structured cnfs to obdds"
    - "lower bounds for exact model counting and applications in probabilistic databases"
    - "a knowledge compilation map"

Connected through hyperedge HE-2 (induced by source paper "graph width measures for cnf encodings with auxiliary variables"):
  with members:
    - "connecting knowledge compilation classes and width parameters"
    - "qbf as an alternative to courcelle s theorem"
    - "connecting width and structure in knowledge compilation"
    - "understanding model counting for beta acyclic cnf formulas"
    - "strong backdoors to bounded treewidth sat"
    - "a knowledge compilation map"

Connected through hyperedge HE-3 (induced by source paper "revisiting graph width measures for cnf encodings"):
  with members:
    - "connecting knowledge compilation classes and width parameters"
    - "qbf as an alternative to courcelle s theorem"
    - "connecting width and structure in knowledge compilation"
    - "model counting for formulas of bounded clique width"
    - "strong backdoors to bounded treewidth sat"
    - "a knowledge compilation map"

Connected through hyperedge HE-4 (induced by source paper "solving a special case of the intensional vs extensional conjecture in probabilistic databases"):
  with members:
    - "towards deterministic decomposable circuits for safe queries"
    - "the language of search"

Connected through hyperedge HE-5 (induced by source paper "towards deterministic decomposable circuits for safe queries"):
  with members:
    - "counting inequivalent monotone boolean functions"
    - "the language of search"

Connected through hyperedge HE-6 (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"
    - "tractable lineages on treelike instances limits and extensions"
    - "sdds are exponentially more succinct than obdds"

Connected through hyperedge HE-7 (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"
    - "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"
    - "lower bounds for exact model counting and applications in probabilistic databases"
    - "the language of search"

Connected through hyperedge HE-8 (induced by source paper "knowledge compilation width and quantification"):
  with members:
    - "exploiting treewidth for projected model counting and its limits"
    - "solving maxsat and sat on structured cnf formulas"
    - "understanding model counting for beta acyclic cnf formulas"

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.LO(Logic in Computer Science)