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 partition based relaxation for steiner trees"
  Abstract: The Steiner tree problem is a classical NP-hard optimization problem with a wide range of practical applications. In an instance of this problem, we are given an undirected graph G=(V,E), a set of terminals R, and non-negative costs c_e for all edges e in E. Any tree that contains all terminals is called a Steiner tree; the goal is to find a minimum-cost Steiner tree. The nodes V R are called Steiner nodes. #R##N#The best approximation algorithm known for the Steiner tree problem is due to Robins and Zelikovsky (SIAM J. Discrete Math, 2005); their greedy algorithm achieves a performance guarantee of 1+(ln 3)/2 ~ 1.55. The best known linear (LP)-based algorithm, on the other hand, is due to Goemans and Bertsimas (Math. Programming, 1993) and achieves an approximation ratio of 2-2/|R|. In this paper we establish a link between greedy and LP-based approaches by showing that Robins and Zelikovsky's algorithm has a natural primal-dual interpretation with respect to a novel partition-based linear programming relaxation. We also exhibit surprising connections between the new formulation and existing LPs and we show that the new LP is stronger than the bidirected cut formulation. #R##N#An instance is b-quasi-bipartite if each connected component of G R has at most b vertices. We show that Robins' and Zelikovsky's algorithm has an approximation ratio better than 1+(ln 3)/2 for such instances, and we prove that the integrality gap of our LP is between 8/7 and (2b+1)/(b+1).

Connected through hyperedge HE-1 (induced by source paper "simplex based steiner tree instances yield large integrality gaps for the bidirected cut relaxation"):
  with members:
    - "hypergraphic lp relaxations for steiner trees"

Connected through hyperedge HE-2 (induced by source paper "polylogarithmic approximation algorithm for k connected directed steiner tree on quasi bipartite graphs"):
  with members:
    - "a quasi polynomial algorithm for submodular tree orienteering in directed graphs"
    - "a logarithmic integrality gap bound for directed steiner tree in quasi bipartite graphs"
    - "approximating directed steiner problems via tree embedding"
    - "analytical approach to parallel repetition"
    - "parameters of two prover one round game and the hardness of connectivity problems"
    - "an improved approximation algorithm for the minimum cost subset k connected subgraph problem"
    - "approximating subset k connectivity problems"
    - "directed steiner tree and the lasserre hierarchy"

Connected through hyperedge HE-3 (induced by source paper "strong steiner tree approximations in practice"):
  with members:
    - "dijkstra meets steiner a fast exact goal oriented steiner tree algorithm"
    - "a robust and scalable algorithm for the steiner problem in graphs"
    - "approximation algorithms for steiner tree problems based on universal solution frameworks"
    - "speeding up dynamic programming with representative sets an experimental evaluation of algorithms for steiner tree on tree decompositions"
    - "hypergraphic lp relaxations for steiner trees"

Connected through hyperedge HE-4 (induced by source paper "matroids and integrality gaps for hypergraphic steiner tree relaxations"):
  with members:
    - "hypergraphic lp relaxations for steiner trees"

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)