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 "anticipatory networking in future generation mobile networks a survey"):
  Abstract: A growing trend for information technology is to not just react to changes, but as much as possible anticipate them. This paradigm made modern solutions such as recommendation systems a ubiquitous presence in today's digital transactions. Anticipatory networking extends the idea to communication technologies by studying patterns and periodicity in human behavior and network dynamics to optimize network performance. This survey collects and analyzes recent papers leveraging context information to forecast the evolution of network conditions and, in turn, to improve network performance. In particular, we identify the main prediction and optimization tools adopted in this body of work and link them with objectives and constraints of the typical applications and scenarios. Finally, we consider open challenges and research directions to make anticipatory networking part of next generation networks.

Includes members:
  Member "kernel based adaptive online reconstruction of coverage maps with side information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "boosting vehicle to cloud communication by machine learning enabled context prediction")
  Member "spatial wireless channel prediction under location uncertainty":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deep learning and gaussian process based band assignment in dual band systems")
  Member "living on the edge the role of proactive caching in 5g wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "aoi delay tradeoff in mobile edge caching with freshness aware content refreshing")
  Member "predictive green wireless access exploiting mobility and application information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "energy efficient predictive resource allocation for vod and real time services")
  Member "rate adaptation and admission control for video transmission with subjective quality constraints":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards physiology aware dash bandwidth compliant prioritized clinical multimedia communication in ambulances")
  Member "predicting a user s next cell with supervised learning based on channel states":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a survey of anticipatory mobile networking context based classification prediction methodologies and optimization techniques")
  Member "a comparative study of collaborative filtering algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "interaction aware factorization machines for recommender systems")
  Member "femtocaching wireless video content delivery through distributed caching helpers":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "cache allocations for consecutive requests of categorized contents service provider s perspective")

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.NI(Networking and Internet Architecture)