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: "recursive n gram hashing is pairwise independent at best"
  Abstract: Many applications use sequences of n consecutive symbols (n-grams). Hashing these n-grams can be a performance bottleneck. For more speed, recursive hash families compute hash values by updating previous values. We prove that recursive hash families cannot be more than pairwise independent. While hashing by irreducible polynomials is pairwise independent, our implementations either run in time O(n) or use an exponential amount of memory. As a more scalable alternative, we make hashing by cyclic polynomials pairwise independent by ignoring n-1 bits. Experimentally, we show that hashing by cyclic polynomials is twice as fast as hashing by irreducible polynomials. We also show that randomized Karp-Rabin hash families are not pairwise independent.

Connected through hyperedge HE-1 (induced by source paper "practical evaluation of lempel ziv 78 and lempel ziv welch tries"):
  with members:
    - "dynamic space efficient hashing"
    - "compression with the tudocomp framework"
    - "faster 64 bit universal hashing using carry less multiplications"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "range predecessor and lempel ziv parsing"
    - "lempel ziv computation in compressed space lz cics"
    - "alphabet dependent string searching with wexponential search trees"
    - "lightweight lempel ziv parsing"

Connected through hyperedge HE-2 (induced by source paper "regular and almost universal hashing an efficient implementation"):
  with members:
    - "faster 64 bit universal hashing using carry less multiplications"
    - "high speed hashing for integers and strings"
    - "strongly universal string hashing is fast"
    - "the universality of iterated hashing over variable length strings"

Connected through hyperedge HE-3 (induced by source paper "twopaco an efficient algorithm to build the compacted de bruijn graph from many complete genomes"):
  with members:
    - "read mapping on de bruijn graphs"
    - "a representation of a compressed de bruijn graph for pan genome analysis that enables search"
    - "kmc 2 fast and resource frugal k mer counting"
    - "using cascading bloom filters to improve the memory usage for de brujin graphs"

Connected through hyperedge HE-4 (induced by source paper "strongly universal string hashing is fast"):
  with members:
    - "explicit and efficient hash families suffice for cuckoo hashing with a stash"
    - "fast set intersection in memory"
    - "the power of simple tabulation hashing"

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.DB(Databases)