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: "the computational landscape of permutation patterns"
  Abstract: In the last years, different types of patterns in permutations have been studied: vincular, bivincular and mesh patterns, just to name a few. Every type of permutation pattern naturally defines a corresponding computational problem: Given a pattern P and a permutation T (the text), is P contained in T? In this paper we draw a map of the computational landscape of permutation pattern matching with different types of patterns. We provide a classical complexity analysis and investigate the impact of the pattern length on the computational hardness. Furthermore, we highlight several directions in which the study of computational aspects of permutation patterns could evolve.

Connected through hyperedge HE-1 (induced by source paper "counting small permutation patterns"):
  with members:
    - "faster and simpler algorithms for finding large patterns in permutations"
    - "finding and counting permutations via csps"
    - "improved bounds for testing forbidden order patterns"
    - "finding small patterns in permutations in linear time"
    - "a fast algorithm for permutation pattern matching based on alternating runs"
    - "hereditary properties of permutations are strongly testable"
    - "orthogonal range searching on the ram revisited"

Connected through hyperedge HE-2 (induced by source paper "finding and counting permutations via csps"):
  with members:
    - "improved bounds for testing forbidden order patterns"
    - "pattern avoiding access in binary search trees"
    - "hitting set for hypergraphs of low vc dimension"
    - "finding small patterns in permutations in linear time"
    - "a fast algorithm for permutation pattern matching based on alternating runs"

Connected through hyperedge HE-3 (induced by source paper "faster and simpler algorithms for finding large patterns in permutations"):
  with members:
    - "improved bounds for testing forbidden order patterns"
    - "pattern avoiding access in binary search trees"
    - "finding small patterns in permutations in linear time"
    - "a fast algorithm for permutation pattern matching based on alternating runs"

Connected through hyperedge HE-4 (induced by source paper "pattern avoiding access in binary search trees"):
  with members:
    - "greedy is an almost optimal deque"
    - "self adjusting binary search trees what makes them tick"
    - "combining binary search trees"
    - "in pursuit of the dynamic optimality conjecture"
    - "upper bounds for maximally greedy binary search trees"
    - "improved bounds and new techniques for davenport schinzel sequences and their generalizations"
    - "splay trees davenport schinzel sequences and the deque conjecture"

Connected through hyperedge HE-5 (induced by source paper "fast algorithms for finding pattern avoiders and counting pattern occurrences in permutations"):
  with members:
    - "finding small patterns in permutations in linear time"
    - "order preserving matching"
    - "a fast algorithm for permutation pattern matching based on alternating runs"

Connected through hyperedge HE-6 (induced by source paper "kernelization lower bound for permutation pattern matching"):
  with members:
    - "finding small patterns in permutations in linear time"
    - "a fast algorithm for permutation pattern matching based on alternating runs"
    - "cross composition a new technique for kernelization lower bounds"

Connected through hyperedge HE-7 (induced by source paper "a fast algorithm for permutation pattern matching based on alternating runs"):
  with members:
    - "finding small patterns in permutations in linear time"
    - "order preserving pattern matching with k mismatches"
    - "order preserving matching"

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.CC(Computational Complexity)