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: "multiscale approach for the network compression friendly ordering"
  Abstract: We present a fast multiscale approach for the network minimum logarithmic arrangement problem. This type of arrangement plays an important role in a network compression and fast node/link access operations. The algorithm is of linear complexity and exhibits good scalability which makes it practical and attractive for using on large-scale instances. Its effectiveness is demonstrated on a large set of real-life networks. These networks with corresponding best-known minimization results are suggested as an open benchmark for a research community to evaluate new methods for this problem.

Connected through hyperedge HE-1 (induced by source paper "survey and taxonomy of lossless graph compression and space efficient graph representations"):
  with members:
    - "grammar based graph compression"
    - "compressing networks with super nodes"
    - "graphzip dictionary based compression for mining graph streams"
    - "parallel construction of compact planar embeddings"
    - "compressed representation of dynamic binary relations with applications"
    - "a succinct data structure for self indexing ternary relations"
    - "fully dynamic de bruijn graphs"
    - "compressing graphs and indexes with recursive graph bisection"

Connected through hyperedge HE-2 (induced by source paper "multiscale planar graph generation"):
  with members:
    - "single and multi level network sparsification by algebraic distance"
    - "generating realistic scaled complex networks"
    - "generating scaled replicas of real world complex networks"
    - "networkit an interactive tool suite for high performance network analysis"
    - "a multilevel bilinear programming algorithm for the vertex separator problem"
    - "recent advances in graph partitioning"
    - "community structure and scale free collections of erdős renyi graphs"
    - "advanced coarsening schemes for graph partitioning"

Connected through hyperedge HE-3 (induced by source paper "moliere automatic biomedical hypothesis generation system"):
  with members:
    - "scalable dynamic topic modeling with clustered latent dirichlet allocation clda"
    - "enriching word vectors with subword information"
    - "bag of tricks for efficient text classification"
    - "scalable topical phrase mining from text corpora"
    - "efficient estimation of word representations in vector space"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-4 (induced by source paper "engineering multilevel support vector machines"):
  with members:
    - "a pso and pattern search based memetic algorithm for svms parameters optimization"
    - "a divide and conquer solver for kernel support vector machines"
    - "advanced coarsening schemes for graph partitioning"
    - "fast response to infection spread and cyber attacks on large scale networks"
    - "relaxation based coarsening and multiscale graph organization"
    - "multi level algorithms for modularity clustering"

Connected through hyperedge HE-5 (induced by source paper "compressing graphs and indexes with recursive graph bisection"):
  with members:
    - "a survey on methods and systems for graph compression"
    - "layered label propagation a multiresolution coordinate free ordering for compressing social networks"

Connected through hyperedge HE-6 (induced by source paper "parallel wavelet tree construction"):
  with members:
    - "parallelism in randomized incremental algorithms"
    - "parallel local graph clustering"
    - "sorting with asymmetric read and write costs"
    - "efficient algorithms with asymmetric read and write costs"
    - "wavelet trees meet suffix trees"
    - "counting triangles in massive graphs with mapreduce"
    - "parallel graph decompositions using random shifts"
    - "skew strikes back new developments in the theory of join algorithms"

Connected through hyperedge HE-7 (induced by source paper "recent advances in graph partitioning"):
  with members:
    - "on the parameterized complexity of computing balanced partitions in graphs"
    - "semi external algorithms for graph partitioning and clustering"
    - "tree based coarsening and partitioning of complex networks"
    - "a multilevel bilinear programming algorithm for the vertex separator problem"
    - "parallel graph partitioning for complex networks"
    - "algorithms for mapping parallel processes onto grid and torus architectures"
    - "partitioning complex networks via size constrained clustering"
    - "community detection and graph partitioning"

Connected through hyperedge HE-8 (induced by source paper "optimal hierarchical layouts for cache oblivious search trees"):
  with members:
    - "don t thrash how to cache your hash on flash"
    - "optimal cache oblivious mesh layouts"

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)