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 "streaming communication protocols"):
  Abstract: We define the Streaming Communication model that combines the main aspects of communication complexity and streaming. We consider two agents that want to compute some function that depends on inputs that are distributed to each agent. The inputs arrive as data streams and each agent has a bounded memory. Agents are allowed to communicate with each other and also update their memory based on the input bit they read and the previous message they received. #R##N#We provide tight tradeoffs between the necessary resources, i.e. communication and memory, for some of the canonical problems from communication complexity by proving a strong general lower bound technique. Second, we analyze the Approximate Matching problem and show that the complexity of this problem (i.e. the achievable approximation ratio) in the one-way variant of our model is strictly different both from the streaming complexity and the one-way communication complexity thereof.

Includes members:
  Member "maximum matching in turnstile streams":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "two player hidden pointer chasing and multi pass lower bounds in turnstile streams")
  Member "improved algorithms for distributed entropy monitoring":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "weighted reservoir sampling from distributed streams")
  Member "better bounds for matchings in the streaming model":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "two player hidden pointer chasing and multi pass lower bounds in turnstile streams")
  Member "randomized algorithms for tracking distributed count frequencies and ranks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards optimal moment estimation in streaming and distributed models")
  Member "tight bounds for distributed functional monitoring":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards optimal moment estimation in streaming and distributed models")
  Member "recognizing well parenthesized expressions in the streaming model":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "memory augmented recurrent neural networks can learn generalized dyck languages")
  Member "continuous monitoring of distributed data streams over a time based sliding window":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "numerical linear algebra in the sliding window model")
  Member "optimal tracking of distributed heavy hitters and quantiles":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on the power of multiple anonymous messages")

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.CC(Computational Complexity)