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: "a learning based approach to joint content caching and recommendation at base stations"
  Abstract: Recommendation system is able to shape user demands, which can be used for boosting caching gain. In this paper, we jointly optimize content caching and recommendation at base stations. We first propose a model to capture the impact of recommendation on user demands, which is controlled by a user-specific threshold. We then formulate a joint caching and recommendation problem maximizing the cache-hit ratio, which is NP-hard. To solve the problem efficiently, we develop a greedy algorithm. Since the user threshold is unknown in practice, we proceed to propose an $\epsilon$-greedy algorithm to learn the threshold via interactions with users. Simulation results show that the greedy algorithm achieves near-optimal performance and improves the cache-hit ratio significantly compared with priori works with/without recommendation. The $\epsilon$-greedy algorithm learns the user threshold quickly, and achieves more than $1-\epsilon$ of the cache-hit ratio obtained by the greedy algorithm with known user threshold.

Connected through hyperedge HE-1 (induced by source paper "the order of things position aware network friendly recommendations in long viewing sessions"):
  with members:
    - "cabaret leveraging recommendation systems for mobile edge caching"
    - "show me the cache optimizing cache friendly recommendations for sequential content access"
    - "wireless caching technical misconceptions and business barriers"
    - "soft cache hits and the impact of alternative content recommendations on mobile edge caching"
    - "making recommendations bandwidth aware"
    - "fundamental limits of caching in wireless d2d networks"
    - "femtocaching wireless video content delivery through distributed caching helpers"

Connected through hyperedge HE-2 (induced by source paper "show me the cache optimizing cache friendly recommendations for sequential content access"):
  with members:
    - "effects of content popularity on the performance of content centric opportunistic networking an analytical approach and applications"
    - "collaborative multi bitrate video caching and processing in mobile edge computing networks"
    - "soft cache hits and the impact of alternative content recommendations on mobile edge caching"
    - "placing dynamic content in caches with small population"
    - "finite length analysis of caching aided coded multicasting"
    - "living on the edge the role of proactive caching in 5g wireless networks"
    - "fundamental limits of caching"
    - "relieving the wireless infrastructure when opportunistic networks meet guaranteed delays"

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.NI(Networking and Internet Architecture)