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: "improved approximation algorithm for fault tolerant facility placement"
  Abstract: We consider the Fault-Tolerant Facility Placement problem ($FTFP$), which is a generalization of the classical Uncapacitated Facility Location problem ($UFL$). In the $FTFP$ problem we have a set of clients $C$ and a set of facilities $F$. Each facility $i \in F$ can be opened many times. For each opening of facility $i$ we pay $f_i \geq 0$. Our goal is to connect each client $j \in C$ with $r_j \geq 1$ open facilities in a way that minimizes the total cost of open facilities and established connections. #R##N#In a series of recent papers $FTFP$ was essentially reduced to $FTFL$ and then to $UFL$ showing it could be approximated with ratio $1.575$. In this paper we show that $FTFP$ can actually be approximated even better. We consider approximation ratio as a function of $r = min_{j \in C} r_j$ (minimum requirement of a client). With increasing $r$ the approximation ratio of our algorithm $\lambda_r$ converges to one. Furthermore, for $r > 1$ the value of $\lambda_r$ is less than 1.463 (hardness of approximation of $UFL$). We also show a lower bound of 1.278 for the approximability of the Fault-Tolerant Facility Location problem ($FTFL$) for arbitrary $r$. Already for $r > 3$ we obtain that $FTFP$ can be approximated with ratio 1.275, showing that under standard complexity theoretic assumptions $FTFP$ is strictly better approximable than $FTFL$.

Connected through hyperedge HE-1 (induced by source paper "a constant factor approximation algorithm for fault tolerant k median"):
  with members:
    - "a unified framework for clustering constrained data without locality property"
    - "an improved approximation for k median and positive correlation in budgeted optimization"
    - "approximating k median via pseudo approximation"
    - "lp rounding algorithms for the fault tolerant facility placement problem"
    - "fault tolerant facility location a randomized dependent lp rounding algorithm"
    - "greedy facility location algorithms analyzed using dual fitting with factor revealing lp"

Connected through hyperedge HE-2 (induced by source paper "lp rounding algorithms for the fault tolerant facility placement problem"):
  with members:
    - "a constant factor approximation algorithm for fault tolerant k median"
    - "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)