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: "productive corecursion in logic programming"
  Abstract: Logic Programming is a Turing complete language. As a consequence, designing algorithms that decide termination and non-termination of programs or decide inductive/coinductive soundness of formulae is a challenging task. For example, the existing state-of-the-art algorithms can only semi-decide coinductive soundness of queries in logic programming for regular formulae. Another, less famous, but equally fundamental and important undecidable property is productivity. If a derivation is infinite and coinductively sound, we may ask whether the computed answer it determines actually computes an infinite formula. If it does, the infinite computation is productive. This intuition was first expressed under the name of computations at infinity in the 80s. In modern days of the Internet and stream processing, its importance lies in connection to infinite data structure processing. #R##N#Recently, an algorithm was presented that semi-decides a weaker property -- of productivity of logic programs. A logic program is productive if it can give rise to productive derivations. In this paper we strengthen these recent results. We propose a method that semi-decides productivity of individual derivations for regular formulae. Thus we at last give an algorithmic counterpart to the notion of productivity of derivations in logic programming. This is the first algorithmic solution to the problem since it was raised more than 30 years ago. We also present an implementation of this algorithm.

Connected through hyperedge HE-1 (induced by source paper "coinduction in uniform foundations for corecursive proof search with horn clauses"):
  with members:
    - "coinductive uniform proofs"
    - "towards coinductive theory exploration in horn clause logic position paper"
    - "breaking the loop recursive proofs for coinductive predicates in fibrations"
    - "guarded dependent type theory with coinductive types"
    - "proof relevant corecursive resolution"
    - "refinement type inference via horn constraint optimization"
    - "sequent calculus in the topos of trees"
    - "first steps in synthetic guarded domain theory step indexing in the topos of trees"

Connected through hyperedge HE-2 (induced by source paper "coinductive uniform proofs"):
  with members:
    - "type theory based on dependent inductive and coinductive types"
    - "proof relevant corecursive resolution"
    - "refinement type inference via horn constraint optimization"
    - "combining deduction modulo and logics of fixed point definitions"
    - "inductive and coinductive components of corecursive functions in coq"

Connected through hyperedge HE-3 (induced by source paper "towards coinductive theory exploration in horn clause logic position paper"):
  with members:
    - "proof relevant corecursive resolution"

Connected through hyperedge HE-4 (induced by source paper "structural resolution for abstract compilation of object oriented languages"):
  with members:
    - "a productivity checker for 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-5 (induced by source paper "logic programming laxness and saturation"):
  with members:
    - "a productivity checker for 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-6 (induced by source paper "a productivity checker for logic programming"):
  with members:
    - "operational semantics of resolution and productivity in horn clause logic"
    - "structural resolution for logic programming"
    - "structural resolution a framework for coinductive proof search and proof construction in horn clause logic"
    - "exploiting parallelism in coalgebraic logic programming"
    - "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.LO(Logic in Computer Science)