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: "constraint solving via fractional edge covers"
  Abstract: Many important combinatorial problems can be modeled as constraint satisfaction problems. Hence identifying polynomial-time solvable classes of constraint satisfaction problems has received a lot of attention. In this paper, we are interested in structural properties that can make the problem tractable. So far, the largest structural class that is known to be polynomial-time solvable is the class of bounded hypertree width instances introduced by Gottlob et al. Here we identify a new class of polynomial-time solvable instances: those having bounded fractional edge cover number. #R##N#Combining hypertree width and fractional edge cover number, we then introduce the notion of fractional hypertree width. We prove that constraint satisfaction problems with bounded fractional hypertree width can be solved in polynomial time (provided that a the tree decomposition is given in the input). Together with a recent approximation algorithm for finding such decompositions by Marx, it follows that bounded fractional hypertree width is now the most general known structural property that guarantees polynomial-time solvability.

Connected through hyperedge HE-1 (induced by source paper "complexity analysis of general and fractional hypertree decompositions"):
  with members:
    - "hyperbench a benchmark and tool for hypergraphs and empirical findings"
    - "tree projections and constraint optimization problems fixed parameter tractability and parallel algorithms"
    - "size bounds and query plans for relational joins"
    - "an analytical study of large sparql query logs"
    - "old techniques for new join algorithms a case study in rdf processing"
    - "general and fractional hypertree decompositions hard and easy cases"
    - "myhill nerode methods for hypergraphs"
    - "faq questions asked frequently"

Connected through hyperedge HE-2 (induced by source paper "constant delay enumeration with fpt preprocessing for conjunctive queries of bounded submodular width"):
  with members:
    - "enumeration on trees under relabelings"
    - "answering fo mod queries under updates on bounded degree databases"
    - "covers of query results"
    - "answering conjunctive queries under updates"
    - "compressed representations of conjunctive query results"
    - "answering ucqs under updates and in the presence of integrity constraints"
    - "what do shannon type inequalities submodular width and disjunctive datalog have to do with one another"
    - "tractable hypergraph properties for constraint satisfaction and conjunctive queries"

Connected through hyperedge HE-3 (induced by source paper "learning models over relational data a brief tutorial"):
  with members:
    - "a layered aggregate engine for analytics workloads"
    - "incremental techniques for large scale dynamic query processing"
    - "counting triangles under updates in worst case optimal time"
    - "on functional aggregate queries with additive inequalities"
    - "size bounds and query plans for relational joins"
    - "incremental view maintenance with triple lock factorization benefits"
    - "boolean tensor decomposition for conjunctive queries with negation"
    - "building efficient query engines in a high level language"

Connected through hyperedge HE-4 (induced by source paper "rk means fast clustering for relational data"):
  with members:
    - "ac dc in database learning thunderstruck"
    - "strong coresets for k median and subspace approximation goodbye dimension"
    - "on functional aggregate queries with additive inequalities"
    - "coresets for k means and k median clustering and their applications"
    - "worst case optimal join algorithms techniques results and open problems"
    - "clustering high dimensional dynamic data streams"
    - "in database learning with sparse tensors"
    - "juggling functions inside a database"

Connected through hyperedge HE-5 (induced by source paper "optimal algorithms for ranked enumeration of answers to full conjunctive queries"):
  with members:
    - "ranked enumeration of conjunctive query results"
    - "any k anytime top k tree pattern retrieval in labeled graphs"
    - "on functional aggregate queries with additive inequalities"
    - "on the enumeration complexity of unions of conjunctive queries"
    - "size bounds and query plans for relational joins"
    - "covers of query results"
    - "answering conjunctive queries under updates"
    - "what do shannon type inequalities submodular width and disjunctive datalog have to do with one another"

Connected through hyperedge HE-6 (induced by source paper "instance and output optimal parallel algorithms for acyclic joins"):
  with members:
    - "size bounds and query plans for relational joins"
    - "answering conjunctive queries under updates"
    - "worst case optimal algorithms for parallel query processing"
    - "what do shannon type inequalities submodular width and disjunctive datalog have to do with one another"
    - "it s all a matter of degree using degree information to optimize multiway joins"
    - "the input output complexity of triangle enumeration"
    - "skew in parallel query processing"
    - "gym a multiround join algorithm in mapreduce"

Connected through hyperedge HE-7 (induced by source paper "potential maximal cliques parameterized by edge clique cover"):
  with members:
    - "hyperbench a benchmark and tool for hypergraphs and empirical findings"
    - "on the tractability of optimization problems on h graphs"
    - "ranked enumeration of minimal triangulations"
    - "positive instance driven dynamic programming for treewidth"
    - "on distance d independent set and other problems in graphs with few minimal separators"
    - "general and fractional hypertree decompositions hard and easy cases"
    - "on the number of minimal separators in graphs"
    - "algorithms parameterized by vertex cover and modular width through potential maximal cliques"

Connected through hyperedge HE-8 (induced by source paper "approximate counting csp seen from the other side"):
  with members:
    - "a dichotomy theorem for nonuniform csps"
    - "the proof of csp dichotomy conjecture"
    - "approximately counting h colourings is bis hard"
    - "the complexity of approximating conservative counting csps"
    - "the challenges of unbounded treewidth in parameterised subgraph counting problems"
    - "understanding model counting for beta acyclic cnf formulas"
    - "complexity of counting csp with complex weights"
    - "an effective dichotomy for the counting constraint satisfaction problem"

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.DS(Data Structures and Algorithms)