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 "age partitioned bloom filters"):
  Abstract: Bloom filters (BF) are widely used for approximate membership queries over a set of elements. BF variants allow removals, sets of unbounded size or querying a sliding window over an unbounded stream. However, for this last case the best current approaches are dictionary based (e.g., based on Cuckoo Filters or TinyTable), and it may seem that BF-based approaches will never be competitive to dictionary-based ones. In this paper we present Age-Partitioned Bloom Filters, a BF-based approach for duplicate detection in sliding windows that not only is competitive in time-complexity, but has better space usage than current dictionary-based approaches (e.g., SWAMP), at the cost of some moderate slack. APBFs retain the BF simplicity, unlike dictionary-based approaches, important for hardware-based implementations, and can integrate known improvements such as double hashing or blocking. We present an Age-Partitioned Blocked Bloom Filter variant which can operate with 2-3 cache-line accesses per insertion and around 2-4 per query, even for high accuracy filters.

Includes members:
  Member "pay for a sliding bloom filter and get counting distinct elements and entropy for free":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "flattened exponential histogram for sliding window queries over data streams")
  Member "towards intelligent compression in streams a biased reservoir sampling based bloom filter approach":
    also connected through other hyperedges:
      (none)

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)