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: "constructing adjacency arrays from incidence arrays"
  Abstract: Graph construction, a fundamental operation in a data processing pipeline, is typically done by multiplying the incidence array representations of a graph, E in and E out, to produce an adjacency array of the graph, A, that can be processed with a variety of algorithms. This paper provides the mathematical criteria to determine if the product A = E T\out E in will have the required structure of the adjacency array of the graph. The values in the resulting adjacency array are determined by the corresponding addition ⊕ and multiplication ⊗ operations used to perform the array multiplication. Illustrations of the various results possible from different ⊕ and ⊗ operations are provided using a small collection of popular music metadata.

Connected through hyperedge HE-1 (induced by source paper "design generation and validation of extreme scale power law graphs"):
  with members:
    - "streaming graph challenge stochastic block partition"
    - "distributed triangle counting in the graphulo matrix math library"
    - "preconditioned spectral clustering for stochastic block partition streaming graph challenge preliminary version at arxiv"
    - "an ensemble framework for detecting community changes in dynamic networks"
    - "scaling in internet traffic a 14 year and 3 day longitudinal study with multiscale analyses and random projections"
    - "static graph challenge subgraph isomorphism"
    - "enabling massive deep neural networks with the graphblas"
    - "pagerank pipeline benchmark proposal for a holistic system benchmark for big data platforms"

Connected through hyperedge HE-2 (induced by source paper "polystore mathematics of relational algebra"):
  with members:
    - "version 0 1 of the bigdawg polystore system"
    - "laradb a minimalist kernel for linear and relational algebra computation"
    - "d4m 3 0 extended database and language capabilities"
    - "bigdawg polystore release and demonstration"
    - "associative array model of sql nosql and newsql databases"
    - "the bigdawg polystore system and architecture"
    - "julia implementation of the dynamic distributed dimensional data model"
    - "graphulo implementation of server side sparse matrix multiply in the accumulo database"

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)