human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "constant factor approximation algorithms for parity constrained facility location problems"):
  Abstract: Facility location is a prominent optimization problem that has inspired a large quantity of both theoretical and practical studies in combinatorial optimization. Although the problem has been investigated under various settings reflecting typical structures within the optimization problems of practical interest, little is known on how the problem behaves in conjunction with parity constraints. This shortfall of understanding was rather disturbing when we consider the central role of parity in the field of combinatorics. In this paper, we present the first constant-factor approximation algorithm for the facility location problem with parity constraints. We are given as the input a metric on a set of facilities and clients, the opening cost of each facility, and the parity requirement--odd, even, or unconstrained--of every facility in this problem. The objective is to open a subset of facilities and assign every client to an open facility so as to minimize the sum of the total opening costs and the assignment distances, but subject to the condition that the number of clients assigned to each open facility must have the same parity as its requirement. #R##N#Although the unconstrained facility location problem as a relaxation for this parity-constrained generalization has unbounded gap, we demonstrate that it yields a structured solution whose parity violation can be corrected at small cost. This correction is prescribed by a T-join on an auxiliary graph constructed by the algorithm. This graph does not satisfy the triangle inequality, but we show that a carefully chosen set of shortcutting operations leads to a cheap and sparse T-join. Finally, we bound the correction cost by exhibiting a combinatorial multi-step construction of an upper bound. We also present the first constant-factor approximation algorithm for the parity-constrained k-center problem, the bottleneck optimization variant.

Includes members:
  Member "a tree structure for dynamic facility location":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the power of recourse better algorithms for facility location in online and dynamic models")
  Member "on facility location with general lower bounds":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "facility location problem in differential privacy model revisited")
  Member "online facility location with deletions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the power of recourse better algorithms for facility location in online and dynamic models")
  Member "optimal parameterized algorithms for planar facility location problems using voronoi diagrams":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "grundy coloring friends half graphs bicliques")
  Member "facility location in evolving metrics":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the power of recourse better algorithms for facility location in online and dynamic models")
  Member "lp based algorithms for capacitated facility location":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "easy capacitated facility location problems with connections to lot sizing")
  Member "eight fifth approximation for the path tsp":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reducing path tsp to tsp")
  Member "local search based approximation algorithms for mobile facility location problems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "sets clustering")

Question: Please tell me which class the source paper 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)