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: "succinct dictionary matching with no slowdown"
  Abstract: The problem of dictionary matching is a classical problem in string matching: given a set S of d strings of total length n characters over an (not necessarily constant) alphabet of size σ, build a data structure so that we can match in a any text T all occurrences of strings belonging to S. The classical solution for this problem is the Aho-Corasick automaton which finds all occ occurrences in a text T in time O(|T| + occ) using a representation that occupies O(m log m) bits of space where m ≤ n + 1 is the number of states in the automaton. In this paper we show that the Aho-Corasick automaton can be represented in just m(log σ + O(1)) + O(d log(n/d)) bits of space while still maintaining the ability to answer to queries in O(|T|+ occ) time. To the best of our knowledge, the currently fastest succinct data structure for the dictionary matching problem uses O(n log σ) bits of space while answering queries in O(|T| log log n + occ) time. In the paper we also show how the space occupancy can be reduced to m(H0+O(1))+O(d log(n/d)) where H0 is the empirical entropy of the characters appearing in the trie representation of the set S, provided that σ < me for any constant 0 < e < 1. The query time remains unchanged.

Connected through hyperedge HE-1 (induced by source paper "on the hardness and inapproximability of recognizing wheeler graphs"):
  with members:
    - "on prefix sorting finite automata"
    - "tunneling on wheeler graphs"

Connected through hyperedge HE-2 (induced by source paper "compressed multiple pattern matching"):
  with members:
    - "greedy shortest common superstring approximation in compact space"
    - "dictionary matching in a stream"
    - "engineering small space dictionary matching"
    - "fixed block compression boosting in fm indexes"
    - "large alphabets and incompressibility"

Connected through hyperedge HE-3 (induced by source paper "parameterized pattern matching succinctly"):
  with members:
    - "linear time construction of compressed text indices in compact space"
    - "parameterized matching in the streaming model"
    - "new algorithms on wavelet trees and applications to information retrieval"

Connected through hyperedge HE-4 (induced by source paper "faster lightweight lempel ziv parsing"):
  with members:
    - "lempel ziv computation in small space lz ciss"
    - "lempel ziv factorization may be harder than computing all runs"
    - "lightweight lempel ziv parsing"
    - "faster compact on line lempel ziv factorization"
    - "fully functional static and dynamic succinct trees"

Connected through hyperedge HE-5 (induced by source paper "worst case efficient single and multiple string matching in the ram model"):
  with members:
    - "fast searching in packed strings"

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.DS(Data Structures and Algorithms)