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: "continuous monitoring of distributed data streams over a time based sliding window"
  Abstract: The past decade has witnessed many interesting algorithms for maintaining statistics over a data stream. This paper initiates a theoretical study of algorithms for monitoring distributed data streams over a time-based sliding window (which contains a variable number of items and possibly out-of-order items). The concern is how to minimize the communication between individual streams and the root, while allowing the root, at any time, to be able to report the global statistics of all streams within a given error bound. This paper presents communication-efficient algorithms for three classical statistics, namely, basic counting, frequent items and quantiles. The worst-case communication cost over a window is $O(\frac{k} {\epsilon} \log \frac{\epsilon N}{k})$ bits for basic counting and $O(\frac{k}{\epsilon} \log \frac{N}{k})$ words for the remainings, where $k$ is the number of distributed data streams, $N$ is the total number of items in the streams that arrive or expire in the window, and $\epsilon < 1$ is the desired error bound. Matching and nearly matching lower bounds are also obtained.

Connected through hyperedge HE-1 (induced by source paper "numerical linear algebra in the sliding window model"):
  with members:
    - "nearly optimal distinct elements and heavy hitters on sliding windows"
    - "lectures on randomized numerical linear algebra"
    - "submodular optimization over sliding windows"
    - "sketches for matrix norms faster smaller and more general"
    - "submodular maximization over sliding windows"
    - "online row sampling"
    - "spectral sparsification and regret minimization beyond matrix multiplicative updates"
    - "frequent directions simple and deterministic matrix sketching"

Connected through hyperedge HE-2 (induced by source paper "streaming communication protocols"):
  with members:
    - "maximum matching in turnstile streams"
    - "improved algorithms for distributed entropy monitoring"
    - "better bounds for matchings in the streaming model"
    - "randomized algorithms for tracking distributed count frequencies and ranks"
    - "tight bounds for distributed functional monitoring"
    - "recognizing well parenthesized expressions in the streaming model"
    - "optimal tracking of distributed heavy hitters and quantiles"
    - "on the complexity of processing massive unordered distributed data"

Connected through hyperedge HE-3 (induced by source paper "submodular optimization over sliding windows"):
  with members:
    - "submodular maximization over sliding windows"
    - "the role of social networks in information diffusion"

Connected through hyperedge HE-4 (induced by source paper "improved algorithms for distributed entropy monitoring"):
  with members:
    - "optimal random sampling from distributed streams revisited"
    - "randomized algorithms for tracking distributed count frequencies and ranks"
    - "tight bounds for distributed functional monitoring"
    - "optimal tracking of distributed heavy hitters and quantiles"
    - "sketching and streaming entropy via approximation theory"
    - "streaming and sublinear approximation of entropy and information distances"

Connected through hyperedge HE-5 (induced by source paper "randomized algorithms for tracking distributed count frequencies and ranks"):
  with members:
    - "optimal random sampling from distributed streams revisited"
    - "tight bounds for distributed functional monitoring"
    - "optimal tracking of distributed heavy hitters and quantiles"

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)