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: "an efficient simulation algorithm on kripke structures"
  Abstract: A number of algorithms for computing the simulation preorder (and equivalence) on Kripke structures are available. Let Sigma denote the state space, -> the transition relation and Psim the partition of Sigma induced by simulation equivalence. While some algorithms are designed to reach the best space bounds, whose dominating additive term is |Psim|^2, other algorithms are devised to attain the best time complexity O(|Psim||->|). We present a novel simulation algorithm which is both space and time efficient: it runs in O(|Psim|^2 log|Psim| + |Sigma|log|Sigma|) space and O(|Psim||->|log|Sigma|) time. Our simulation algorithm thus reaches the best space bounds while closely approaching the best time complexity.

Connected through hyperedge HE-1 (induced by source paper "structural indexing for conjunctive path queries"):
  with members:
    - "the ubiquity of large graphs and surprising challenges of graph processing extended survey"
    - "survey and taxonomy of lossless graph compression and space efficient graph representations"
    - "gmark schema driven generation of graphs and queries"
    - "g core a core for future graph query languages"
    - "an analytical study of large sparql query logs"
    - "foundations of modern query languages for graph databases"
    - "taming subgraph isomorphism for rdf query processing"
    - "similarity and bisimilarity notions appropriate for characterizing indistinguishability in fragments of the calculus of relations"

Connected through hyperedge HE-2 (induced by source paper "foundation for a series of efficient simulation algorithms"):
  with members:
    - "three simulation algorithms for labelled transition systems"
    - "an efficient simulation algorithm based on abstract interpretation"

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)