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: "linview incremental view maintenance for complex analytical queries"
  Abstract: Many analytics tasks and machine learning problems can be naturally expressed by iterative linear algebra programs. In this paper, we study the incremental view maintenance problem for such complex analytical queries. We develop a framework, called LINVIEW, for capturing deltas of linear algebra programs and understanding their computational cost. Linear algebra operations tend to cause an avalanche effect where even very local changes to the input matrices spread out and infect all of the intermediate results and the final view, causing incremental view maintenance to lose its performance benefit over re-evaluation. We develop techniques based on matrix factorizations to contain such epidemics of change. As a consequence, our techniques make incremental view maintenance of linear algebra practical and usually substantially cheaper than re-evaluation. We show, both analytically and experimentally, the usefulness of these techniques when applied to standard analytics tasks. Our evaluation demonstrates the efficiency of LINVIEW in generating parallel incremental programs that outperform re-evaluation techniques by more than an order of magnitude.

Connected through hyperedge HE-1 (induced by source paper "priu a provenance based approach for incrementally updating regression models"):
  with members:
    - "holodetect few shot learning for error detection"
    - "manipulating and measuring model interpretability"
    - "boostclean automated error detection and repair for machine learning"
    - "the mythos of model interpretability"
    - "processing analytical workloads incrementally"
    - "putting lipstick on pig enabling database style workflow provenance"
    - "provenance for aggregate queries"

Connected through hyperedge HE-2 (induced by source paper "bad to the bone big active data at its core"):
  with members:
    - "an idea an ingestion framework for data enrichment in asterixdb"
    - "efficient data ingestion and query processing for lsm based storage systems"
    - "planetsense a real time streaming and spatio temporal analytics platform for gathering geo spatial intelligence from open source data"
    - "asterixdb a scalable open source bdms"

Connected through hyperedge HE-3 (induced by source paper "the linear algebra mapping problem"):
  with members:
    - "automatic generation of efficient linear algebra programs"
    - "clblast a tuned opencl blas library"
    - "the generalized matrix chain algorithm"
    - "image restoration by iterative denoising and backward projections"
    - "recursive algorithms for dense linear algebra the relapack collection"
    - "sparsity based correction of exponential artifacts"
    - "on a natural dynamics for linear programming"
    - "julia a fresh approach to numerical computing"

Connected through hyperedge HE-4 (induced by source paper "incremental techniques for large scale dynamic query processing"):
  with members:
    - "counting triangles under updates in worst case optimal time"
    - "answering fo mod queries under updates on bounded degree databases"
    - "incremental view maintenance with triple lock factorization benefits"
    - "answering conjunctive queries under updates"
    - "answering ucqs under updates and in the presence of integrity constraints"
    - "dbtoaster higher order delta processing for dynamic frequently fresh views"

Connected through hyperedge HE-5 (induced by source paper "a survey of state management in big data processing systems"):
  with members:
    - "elasticutor rapid elasticity for realtime stateful stream processing"
    - "incremental query processing on big data streams"
    - "integrative dynamic reconfiguration in a parallel stream processing engine"
    - "frogwild fast pagerank approximations on graph engines"
    - "incremental computation with names"
    - "s store streaming meets transaction processing"
    - "tolerating correlated failures in massively parallel stream processing engines"
    - "when two choices are not enough balancing at scale in distributed stream processing"

Connected through hyperedge HE-6 (induced by source paper "incremental view maintenance with triple lock factorization benefits"):
  with members:
    - "answering conjunctive queries under updates"
    - "in database learning with sparse tensors"
    - "towards linear algebra over normalized data"
    - "mllib machine learning in apache spark"
    - "faq questions asked frequently"
    - "aggregation and ordering in factorised databases"
    - "skew strikes back new developments in the theory of join algorithms"
    - "the madlib analytics library or mad skills the sql"

Connected through hyperedge HE-7 (induced by source paper "towards linear algebra over normalized data"):
  with members:
    - "tensorflow a system for large scale machine learning"
    - "aggregation and ordering in factorised databases"
    - "the madlib analytics library or mad skills the sql"
    - "towards a unified architecture for in rdbms analytics"
    - "fdb a query engine for factorised relational databases"

Connected through hyperedge HE-8 (induced by source paper "incremental knowledge base construction using deepdive"):
  with members:
    - "from data fusion to knowledge fusion"
    - "logarithmic time updates and queries in probabilistic networks"
    - "feature engineering for knowledge base construction"
    - "errata distant supervision for relation extraction with matrix completion"
    - "dimmwitted a study of main memory statistical analytics"
    - "a convolutional neural network for modelling sentences"
    - "adaptive inference on general graphical models"
    - "incrementally maintaining classification using an rdbms"

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.DB(Databases)