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: "how good is the chord algorithm"
  Abstract: The Chord algorithm is a popular, simple method for the succinct approximation of curves, which is widely used, under different names, in a variety of areas, such as, multiobjective and parametric optimization, computational geometry, and graphics. We analyze the performance of the Chord algorithm, as compared to the optimal approximation that achieves a desired accuracy with the minimum number of points. We prove sharp upper and lower bounds, both in the worst case and average case setting.

Connected through hyperedge HE-1 (induced by source paper "the power of the weighted sum scalarization for approximating multiobjective optimization problems"):
  with members:
    - "approximation algorithms for multi criteria traveling salesman problems"

Connected through hyperedge HE-2 (induced by source paper "clustering time series under the fr echet distance"):
  with members:
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"
    - "on the impossibility of dimension reduction for doubling subsets of ell_p p 2"
    - "approximating k median via pseudo approximation"
    - "four soviets walk the dog with an application to alt s conjecture"
    - "jaywalking your dog computing the fr echet distance with shortcuts"
    - "a unified framework for approximating and clustering data"
    - "approximating the fr echet distance for realistic curves in near linear time"

Connected through hyperedge HE-3 (induced by source paper "the tropical shadow vertex algorithm solves mean payoff games in polynomial time on average"):
  with members:
    - "smoothed analysis of algorithms why the simplex algorithm usually takes polynomial time"

Connected through hyperedge HE-4 (induced by source paper "rita an index tuning advisor for replicated databases"):
  with members:
    - "only aggressive elephants are fast elephants"
    - "cophy a scalable portable and interactive index advisor for large workloads"

Connected through hyperedge HE-5 (induced by source paper "efficiency revenue trade offs in auctions"):
  with members:
    - "from convex optimization to randomized mechanisms toward optimal combinatorial auctions"
    - "an impossibility result for truthful combinatorial auctions with submodular valuations"
    - "optimal auctions with correlated bidders are easy"
    - "efficiency loss in revenue optimal auctions"
    - "efficiency of revenue optimal mechanisms"

Connected through hyperedge HE-6 (induced by source paper "confronting intractability via parameters"):
  with members:
    - "slightly superexponential parameterized problems"
    - "bidimensionality and kernels"
    - "minimizing movement fixed parameter tractability"
    - "dynamic programming for graphs on surfaces"
    - "courcelle s theorem a game theoretic approach"
    - "preprocessing for treewidth a combinatorial analysis through kernelization"
    - "solving connectivity problems parameterized by treewidth in single exponential time"
    - "co nondeterminism in compositions a kernelization lower bound for a ramsey type problem"

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)