human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "quotient hash tables efficiently detecting duplicates in streaming data"):
  Abstract: This article presents the Quotient Hash Table (QHT) a new data structure for duplicate detection in unbounded streams. QHTs stem from a corrected analysis of streaming quotient filters (SQFs), resulting in a 33% reduction in memory usage for equal performance. We provide a new and thorough analysis of both algorithms, with results of interest to other existing constructions.   We also introduce an optimised version of our new data structure dubbed Queued QHT with Duplicates (QQHTD).   We prove in a benchmark that QHT and QQHTD both are, at the same time more efficient and faster than any other filter from the literature, by a large margin.   Finally we discuss the effect of adversarial inputs for hash-based duplicate filters similar to QHT.

Includes members:
  Member "optimal lower bounds for universal relation and for samplers and finding duplicates in streams":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dynamic streaming spectral sparsification in nearly linear time and space")
  Member "bloom filters in adversarial environments":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the adversarial robustness of sampling")
  Member "tight bounds for lp samplers finding duplicates in streams and related problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dynamic streaming spectral sparsification in nearly linear time and space")

Question: Please tell me which class the source paper 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)