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: "on the insertion time of cuckoo hashing"
  Abstract: Cuckoo hashing is an efficient technique for creating large hash tables with high space utilization and guaranteed constant access times. There, each item can be placed in a location given by any one out of k different hash functions. In this paper we investigate further the random walk heuristic for inserting in an online fashion new items into the hash table. Provided that k > 2 and that the number of items in the table is below (but arbitrarily close) to the theoretically achievable load threshold, we show a polylogarithmic bound for the maximum insertion time that holds with high probability.

Connected through hyperedge HE-1 (induced by source paper "balanced allocation through random walk"):
  with members:
    - "on the insertion time of random walk cuckoo hashing"

Connected through hyperedge HE-2 (induced by source paper "horcrux a password manager for paranoids"):
  with members:
    - "sharp load thresholds for cuckoo hashing"

Connected through hyperedge HE-3 (induced by source paper "a simple hash class with strong randomness properties in graphs and hypergraphs"):
  with members:
    - "from independence to expansion and back again"
    - "approximately minwise independence with twisted tabulation"
    - "parallel peeling algorithms"
    - "simple tabulation fast expanders double tabulation and high independence"
    - "on the k independence required by linear probing and minwise independence"
    - "independence of tabulation based hash classes"
    - "tight thresholds for cuckoo hashing via xorsat"

Connected through hyperedge HE-4 (induced by source paper "a faster algorithm for cuckoo insertion and bipartite matching in large graphs"):
  with members:
    - "a simple hash class with strong randomness properties in graphs and hypergraphs"
    - "sharp load thresholds for cuckoo hashing"
    - "de amortized cuckoo hashing provable worst case performance and experimental results"

Connected through hyperedge HE-5 (induced by source paper "consistent hashing with bounded loads"):
  with members:
    - "on the insertion time of random walk cuckoo hashing"
    - "balanced allocations a simple proof for the heavily loaded case"

Connected through hyperedge HE-6 (induced by source paper "on the insertion time of random walk cuckoo hashing"):
  with members:
    - "sharp load thresholds for cuckoo 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.DS(Data Structures and Algorithms)