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 "who should google scholar update more often"):
  Abstract: We consider a resource-constrained updater, such as Google Scholar, which wishes to update the citation records of a group of researchers, who have different mean citation rates (and optionally, different importance coefficients), in such a way to keep the overall citation index as up to date as possible. The updater is resource-constrained and cannot update citations of all researchers all the time. In particular, it is subject to a total update rate constraint that it needs to distribute among individual researchers. We use a metric similar to the age of information: the long-term average difference between the actual citation numbers and the citation numbers according to the latest updates. We show that, in order to minimize this difference metric, the updater should allocate its total update capacity to researchers proportional to the $square$ $roots$ of their mean citation rates. That is, more prolific researchers should be updated more often, but there are diminishing returns due to the concavity of the square root function. More generally, our paper addresses the problem of optimal operation of a resource-constrained sampler that wishes to track multiple independent counting processes in a way that is as up to date as possible.

Includes members:
  Member "optimal selective encoding for timely updates":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "partial updates losing information for freshness")
  Member "trading off computation with transmission in status update systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "partial updates losing information for freshness")
  Member "average peak age of information minimization in uav assisted iot networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimized age of information tail for ultra reliable low latency communications in vehicular networks")
  Member "a reinforcement learning framework for optimizing age of information in rf powered communication systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the age of information in internet of things systems with correlated devices")
  Member "age of information aware cache updating with file and age dependent update durations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "aoi and energy consumption oriented dynamic status updating in caching enabled iot networks")
  Member "reducing age of information for computation intensive messages via packet replacement":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "partial updates losing information for freshness")
  Member "timely distributed computation with stragglers":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "partial updates losing information for freshness")
  Member "age of information in multicast networks with multiple update streams":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "partial updates losing information for freshness")

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.IT(Information Theory)