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: "on line file caching"
  Abstract: In the on-line file-caching problem problem, the input is a sequence of requests for files, given on-line (one at a time). Each file has a non-negative size and a non-negative retrieval cost. The problem is to decide which files to keep in a fixed-size cache so as to minimize the sum of the retrieval costs for files that are not in the cache when requested. The problem arises in web caching by browsers and by proxies. This paper describes a natural generalization of LRU called Landlord and gives an analysis showing that it has an optimal performance guarantee (among deterministic on-line algorithms). #R##N#The paper also gives an analysis of the algorithm in a so-called ``loosely'' competitive model, showing that on a ``typical'' cache size, either the performance guarantee is O(1) or the total retrieval cost is insignificant.

Connected through hyperedge HE-1 (induced by source paper "cache optimization models and algorithms"):
  with members:
    - "learning to cache with no regrets"
    - "introduction to online convex optimization"
    - "cabaret leveraging recommendation systems for mobile edge caching"
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "competitive caching with machine learned advice"
    - "online convex optimization and no regret learning algorithms guarantees and applications"
    - "show me the cache optimizing cache friendly recommendations for sequential content access"
    - "a reinforcement learning approach to proactive caching in wireless networks"

Connected through hyperedge HE-2 (induced by source paper "stochastic dominance and the bijective ratio of online algorithms"):
  with members:
    - "relative worst order analysis a survey"
    - "an optimal randomized online algorithm for reordering buffer management"
    - "a comparison of performance measures for online algorithms"
    - "on line paging against adversarially biased random inputs"
    - "the k server dual and loose competitiveness for paging"

Connected through hyperedge HE-3 (induced by source paper "online tree caching"):
  with members:
    - "compressing ip forwarding tables towards entropy bounds and beyond"
    - "online companion caching"
    - "the k server dual and loose competitiveness for paging"
    - "competitive paging algorithms"

Connected through hyperedge HE-4 (induced by source paper "general caching is hard even with small pages"):
  with members:
    - "a constant factor approximation algorithm for unsplittable flow on paths"
    - "competitive paging algorithms"

Connected through hyperedge HE-5 (induced by source paper "online coded caching"):
  with members:
    - "coded caching for delay sensitive content"
    - "hierarchical coded caching"
    - "coded caching with nonuniform demands"
    - "decentralized coded caching attains order optimal memory rate tradeoff"
    - "fundamental limits of caching"
    - "an equivalence between network coding and index coding"
    - "the k server dual and loose competitiveness for paging"
    - "competitive paging algorithms"

Connected through hyperedge HE-6 (induced by source paper "on randomized memoryless algorithms for the weighted k server problem"):
  with members:
    - "the generalized work function algorithm is competitive for the generalized 2 server problem"
    - "the k server dual and loose competitiveness for paging"

Connected through hyperedge HE-7 (induced by source paper "better algorithms for unfair metrical task systems and applications"):
  with members:
    - "the k server dual and loose competitiveness for paging"
    - "competitive paging algorithms"

Connected through hyperedge HE-8 (induced by source paper "moo a methodology for online optimization through mining the offline optimum"):
  with members:
    - "truly online paging with locality of reference"
    - "competitive paging algorithms"

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.DS(Data Structures and Algorithms)