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 constant factor approximation algorithm for fault tolerant k median"
  Abstract: In this paper, we consider the fault-tolerant $k$-median problem and give the \emph{first} constant factor approximation algorithm for it. In the fault-tolerant generalization of classical $k$-median problem, each client $j$ needs to be assigned to at least $r_j \ge 1$ distinct open facilities. The service cost of $j$ is the sum of its distances to the $r_j$ facilities, and the $k$-median constraint restricts the number of open facilities to at most $k$. Previously, a constant factor was known only for the special case when all $r_j$s are the same, and a logarithmic approximation ratio for the general case. In addition, we present the first polynomial time algorithm for the fault-tolerant $k$-median problem on a path or a HST by showing that the corresponding LP always has an integral optimal solution. #R##N#We also consider the fault-tolerant facility location problem, where the service cost of $j$ can be a weighted sum of its distance to the $r_j$ facilities. We give a simple constant factor approximation algorithm, generalizing several previous results which only work for nonincreasing weight vectors.

Connected through hyperedge HE-1 (induced by source paper "a unified framework for clustering constrained data without locality property"):
  with members:
    - "faster balanced clusterings in high dimension"
    - "faster algorithms for the constrained k means problem"
    - "the hardness of approximation of euclidean k means"
    - "net and prune a linear time algorithm for euclidean distance problems"
    - "parallel algorithms for geometric graph problems"
    - "fault tolerant clustering revisited"
    - "fast clustering with lower bounds no customer too far no shop too small"
    - "lp rounding for k centers with non uniform hard capacities"

Connected through hyperedge HE-2 (induced by source paper "proportional approval voting harmonic k median and negative association"):
  with members:
    - "approximation and parameterized complexity of minimax approval voting"
    - "finding a collective set of items from proportional multirepresentation to group recommendation"
    - "an improved approximation for k median and positive correlation in budgeted optimization"
    - "analytical approach to parallel repetition"
    - "multimode control attacks on elections"

Connected through hyperedge HE-3 (induced by source paper "lp rounding algorithms for the fault tolerant facility placement problem"):
  with members:
    - "improved approximation algorithm for fault tolerant facility placement"
    - "unconstrained and constrained fault tolerant resource allocation"
    - "lp rounding algorithms for facility location problems"
    - "fault tolerant facility location a randomized dependent lp rounding algorithm"
    - "an optimal bifactor approximation algorithm for the metric uncapacitated facility location problem"
    - "greedy facility location algorithms analyzed using dual fitting with factor revealing lp"

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)