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: "a productivity checker for logic programming"
  Abstract: Automated analysis of recursive derivations in logic programming is known to be a hard problem. Both termination and non-termination are undecidable problems in Turing-complete languages. However, some declarative languages offer a practical work-around for this problem, by making a clear distinction between whether a program is meant to be understood inductively or coinductively. For programs meant to be understood inductively, termination must be guaranteed, whereas for programs meant to be understood coinductively, productive non-termination (or "productivity") must be ensured. In practice, such classification helps to better understand and implement some non-terminating computations. #R##N#Logic programming was one of the first declarative languages to make this distinction: in the 1980's, Lloyd and van Emden's "computations at infinity" captured the big-step operational semantics of derivations that produce infinite terms as answers. In modern terms, computations at infinity describe "global productivity" of computations in logic programming. Most programming languages featuring coinduction also provide an observational, or small-step, notion of productivity as a computational counterpart to global productivity. This kind of productivity is ensured by checking that finite initial fragments of infinite computations can always be observed to produce finite portions of their infinite answer terms. #R##N#In this paper we introduce a notion of observational productivity for logic programming as an algorithmic approximation of global productivity, give an effective procedure for semi-deciding observational productivity, and offer an implemented automated observational productivity checker for logic programs.

Connected through hyperedge HE-1 (induced by source paper "structural resolution for abstract compilation of object oriented languages"):
  with members:
    - "productive corecursion in logic programming"
    - "operational semantics of resolution and productivity in horn clause logic"
    - "proof relevant corecursive resolution"
    - "structural resolution for logic programming"
    - "structural resolution a framework for coinductive proof search and proof construction in horn clause logic"
    - "coalgebraic logic programming from semantics to implementation"

Connected through hyperedge HE-2 (induced by source paper "productive corecursion in logic programming"):
  with members:
    - "operational semantics of resolution and productivity in horn clause logic"
    - "proof relevant corecursive resolution"
    - "structural resolution for logic programming"
    - "coalgebraic logic programming from semantics to implementation"
    - "a dynamic approach to characterizing termination of general logic programs"

Connected through hyperedge HE-3 (induced by source paper "structural resolution with co inductive loop detection"):
  with members:
    - "structural resolution for logic programming"
    - "structural resolution a framework for coinductive proof search and proof construction in horn clause logic"
    - "coalgebraic logic programming from semantics to implementation"

Connected through hyperedge HE-4 (induced by source paper "logic programming laxness and saturation"):
  with members:
    - "productive corecursion in logic programming"
    - "operational semantics of resolution and productivity in horn clause logic"
    - "category theoretic semantics for theorem proving in logic programming embracing the laxness"
    - "bialgebraic semantics for logic programming"
    - "proof relevant corecursive resolution"
    - "a type theoretic approach to resolution"
    - "structural resolution for logic programming"
    - "structural resolution a framework for coinductive proof search and proof construction in horn clause logic"

Connected through hyperedge HE-5 (induced by source paper "operational semantics of resolution and productivity in horn clause logic"):
  with members:
    - "proof relevant corecursive resolution"
    - "structural resolution for logic programming"
    - "structural resolution a framework for coinductive proof search and proof construction in horn clause logic"
    - "coalgebraic logic programming from semantics to implementation"

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.PL(Programming Languages)