human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "interaction and depth against nondeterminism in proof search"):
  Abstract: Deep inference is a proof theoretic methodology that generalizes the standard#N#notion of inference of the sequent calculus, whereby inference rules become#N#applicable at any depth inside logical expressions. Deep inference provides#N#more freedom in the design of deductive systems for different logics and a rich#N#combinatoric analysis of proofs. In particular, construction of exponentially#N#shorter analytic proofs becomes possible, however with the cost of a greater#N#nondeterminism than in the sequent calculus. In this paper, we show that the#N#nondeterminism in proof search can be reduced without losing the shorter proofs#N#and without sacrificing proof theoretic cleanliness. For this, we exploit an#N#interaction and depth scheme in the logical expressions. We demonstrate our#N#method on deep inference systems for multiplicative linear logic and classical#N#logic, discuss its proof complexity and its relation to focusing, and present#N#implementations.

Includes members:
  Member "on the proof complexity of deep inference":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "de morgan dual nominal quantifiers modelling private names in non commutative logic")
  Member "a system of interaction and structure":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "de morgan dual nominal quantifiers modelling private names in non commutative logic")
  Member "a system of interaction and structure ii the need for deep inference":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "de morgan dual nominal quantifiers modelling private names in non commutative logic")

Question: Please tell me which class the source paper 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)