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: "list factoring and relative worst order analysis"
  Abstract: Relative worst order analysis is a supplement or alternative to competitive analysis which has been shown to give results more in accordance with observed behavior of online algorithms for a range of different online problems. The contribution of this paper is twofold. First, it adds the static list accessing problem to the collection of online problems where relative worst order analysis gives better results. Second, and maybe more interesting, it adds the non-trivial supplementary proof technique of list factoring to the theoretical toolbox for relative worst order analysis.

Connected through hyperedge HE-1 (induced by source paper "relative worst order analysis a survey"):
  with members:
    - "stochastic dominance and the bijective ratio of online algorithms"
    - "online bounded analysis"
    - "probabilistic analysis of the dual next fit algorithm for bin covering"
    - "relative interval analysis of paging algorithms on access graphs"
    - "the frequent items problem in online streaming under various performance measures"
    - "access graphs results for lru versus fifo under relative worst order analysis"
    - "a comparison of performance measures via online search"
    - "a comparison of performance measures for online algorithms"

Connected through hyperedge HE-2 (induced by source paper "online bounded analysis"):
  with members:
    - "the k server dual and loose competitiveness for paging"

Connected through hyperedge HE-3 (induced by source paper "relative interval analysis of paging algorithms on access graphs"):
  with members:
    - "access graphs results for lru versus fifo under relative worst order analysis"
    - "a comparison of performance measures for online algorithms"
    - "on line paging against adversarially biased random inputs"
    - "truly online paging with locality of reference"
    - "the k server dual and loose competitiveness for paging"

Connected through hyperedge HE-4 (induced by source paper "online bin covering expectations vs guarantees"):
  with members:
    - "relative interval analysis of paging algorithms on access graphs"
    - "access graphs results for lru versus fifo under relative worst order analysis"
    - "a comparison of performance measures via online search"
    - "a comparison of performance measures for online algorithms"

Connected through hyperedge HE-5 (induced by source paper "access graphs results for lru versus fifo under relative worst order analysis"):
  with members:
    - "truly online paging with locality of reference"

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)