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: "enumeration of enumeration algorithms"
  Abstract: In this paper, we enumerate enumeration problems and algorithms. This survey is under construction. If you know some results not in this survey or there is anything wrong, please let me know.

Connected through hyperedge HE-1 (induced by source paper "constant delay enumeration for nondeterministic document spanners"):
  with members:
    - "enumeration on trees with tractable combined complexity and efficient updates"
    - "enumeration on trees under relabelings"
    - "constant delay algorithms for regular document spanners"
    - "answering fo mod queries under updates on bounded degree databases"
    - "a circuit based approach to efficient enumeration"
    - "answering conjunctive queries under updates"
    - "document spanners for extracting incomplete information expressiveness and complexity"
    - "joining extractions of regular expressions"

Connected through hyperedge HE-2 (induced by source paper "enumerating minimal dominating sets in k_t free graphs and variants"):
  with members:
    - "output polynomial enumeration on graphs of bounded local linear mim width"
    - "efficient enumeration of solutions produced by closure operations"
    - "on the enumeration of minimal dominating sets and related notions"
    - "a polynomial delay algorithm for enumerating minimal dominating sets in chordal graphs"
    - "new results on monotone dualization and generating hypergraph transversals"

Connected through hyperedge HE-3 (induced by source paper "efficient enumeration of bipartite subgraphs in graphs"):
  with members:
    - "efficient enumeration of induced subtrees in a k degenerate graph"
    - "optimal listing of cycles and st paths in undirected graphs"
    - "listing all maximal cliques in large sparse real world graphs"
    - "listing all maximal cliques in sparse graphs in near optimal time"

Connected through hyperedge HE-4 (induced by source paper "learning disjunctions of predicates"):
  with members:
    - "learning boolean halfspaces with small weights from membership queries"

Connected through hyperedge HE-5 (induced by source paper "allsat compressed with wildcards part 1 converting cnf s to orthogonal dnf s"):
  with members:
    - "compressed representation of learning spaces"
    - "computing the output distribution and selection probabilities of a stack filter from the dnf of its positive boolean function"
    - "compactly generating all satisfying truth assignments of a horn formula"

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)