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 "on gossip based information dissemination in pervasive recommender systems"):
  Abstract: Pervasive computing systems employ distributed and embedded devices in order to raise, communicate, and process data in an anytime-anywhere fashion. Certainly, its most prominent device is the smartphone due to its wide proliferation, growing computation power, and wireless networking capabilities. In this context, we revisit the implementation of digitalized word-of-mouth that suggests exchanging item preferences between smartphones offline and directly in immediate proximity. Collaboratively and decentrally collecting data in this way has two benefits. First, it allows to attach for instance location-sensitive context information in order to enrich collected item preferences. Second, model building does not require network connectivity. Despite the benefits, the approach naturally raises data privacy and data scarcity issues. In order to address both, we propose Propagate and Filter, a method that translates the traditional approach of finding similar peers and exchanging item preferences among each other from the field of decentralized to that of pervasive recommender systems. Additionally, we present preliminary results on a prototype mobile application that implements the proposed device-to-device information exchange. Average ad-hoc connection delays of 25.9 seconds and reliable connection success rates within 6 meters underpin the approach's technical feasibility.

Includes members:
  Member "affinity a system for latent user similarity comparison on texting data":
    also connected through other hyperedges:
      (none)
  Member "collaborating with users in proximity for decentralized mobile recommender systems":
    also connected through other hyperedges:
      (none)
  Member "context data categories and privacy model for mobile data collection apps":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "affinity a system for latent user similarity comparison on texting data")
  Member "federated meta learning for recommendation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi step model agnostic meta learning convergence and improved algorithms")
  Member "do you like what i like similarity estimation in proximity based mobile social networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "affinity a system for latent user similarity comparison on texting data")
  Member "federated meta learning with fast convergence and efficient communication":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "survey of personalization techniques for federated learning")
  Member "federated learning of deep networks using model averaging":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "neural data server a large scale search engine for transfer learning data")

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.SI(Social and Information Networks)