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 "mining frequent items in unstructured p2p networks"):
  Abstract: Large scale decentralized systems, such as P2P, sensor or IoT device networks are becoming increasingly common, and require robust protocols to address the challenges posed by the distribution of data and the large number of peers belonging to the network. In this paper, we deal with the problem of mining frequent items in unstructured P2P networks. This problem, of practical importance, has many useful applications. We design P2PSS, a fully decentralized, gossip--based protocol for frequent items discovery, leveraging the Space-Saving algorithm. We formally prove the correctness and theoretical error bound. Extensive experimental results clearly show that P2PSS provides very good accuracy and scalability, also in the presence of highly dynamic P2P networks with churning. To the best of our knowledge, this is the first gossip--based distributed algorithm providing strong theoretical guarantees for both the Approximate Frequent Items Problem in Unstructured P2P Networks and for the frequency estimation of discovered frequent items.

Includes members:
  Member "parallel mining of time faded heavy hitters":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "one table to count them all parallel frequency estimation on single board computers")
  Member "a parallel space saving algorithm for frequent items and the hurwitz zeta distribution":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "parallel mining of time faded heavy hitters")
  Member "parallel space saving on multi and many core processors":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "kilograms very large n grams for malware classification")
  Member "fast and accurate mining of correlated heavy hitters":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "parallel mining of time faded heavy hitters")
  Member "mining frequent items in the time fading model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "parallel mining of time faded heavy hitters")
  Member "on the influence of graph density on randomized gossiping":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "probabilistic self stabilization")
  Member "identifying correlated heavy hitters in a two dimensional data stream":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "parallel mining of time faded heavy hitters")

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)