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 novel recursive construction for coded caching schemes"
  Abstract: As a strategy to further reduce the transmission pressure during the peak traffic times in wireless network, coded caching has been widely studied recently. And several coded caching schemes are constructed focusing on the two core problems in practice, i.e., the rate transmitted during the peak traffic times and the packet number of each file divided during the off peak traffic times. It is well known that there exits a tradeoff between the rate and the packet number. In this paper, a novel recursive construction is proposed. As an application, several new schemes are obtained. Comparing with previously known schemes, new schemes could further reduce packet number by increasing little rate. And for some parameters in coded caching systems, the packet number of our new schemes are smaller than that of schemes generated by memory sharing method which is widely used in the field of caching. By the way our new schemes include all the results constructed by Tang et al., (IEEE ISIT, 2790-2794, 2017) as special cases.

Connected through hyperedge HE-1 (induced by source paper "mobility aware coded storage and delivery"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "adding transmitters dramatically boosts coded caching gains for finite file sizes"
    - "delay aware coded caching for mobile users"
    - "novel decentralized coded caching through coded prefetching"
    - "the optimal memory rate trade off for the non uniform centralized caching problem with two files under uncoded placement"
    - "coded caching in a multi server system with random topology"
    - "low subpacketization schemes for coded caching"
    - "optimization of heterogeneous coded caching"

Connected through hyperedge HE-2 (induced by source paper "linear coded caching scheme for centralized networks"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "coded caching via line graphs of bipartite graphs"
    - "placement delivery array design through strong edge coloring of bipartite graphs"
    - "optimal placement delivery arrays with minimum number of rows"
    - "on the placement delivery array design for centralized coded caching scheme"
    - "coded caching with linear subpacketization is possible using ruzsa szem eredi graphs"
    - "coded caching schemes with reduced subpacketization from linear block codes"
    - "uncoded placement optimization for coded delivery"

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.IT(Information Theory)