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: "data polygamy the many many relationships among urban spatio temporal data sets"
  Abstract: The increasing ability to collect data from urban environments, coupled with a push towards openness by governments, has resulted in the availability of numerous spatio-temporal data sets covering diverse aspects of a city. Discovering relationships between these data sets can produce new insights by enabling domain experts to not only test but also generate hypotheses. However, discovering these relationships is difficult. First, a relationship between two data sets may occur only at certain locations and/or time periods. Second, the sheer number and size of the data sets, coupled with the diverse spatial and temporal scales at which the data is available, presents computational challenges on all fronts, from indexing and querying to analyzing them. Finally, it is non-trivial to differentiate between meaningful and spurious relationships. To address these challenges, we propose Data Polygamy, a scalable topology-based framework that allows users to query for statistically significant relationships between spatio-temporal data sets. We have performed an experimental evaluation using over 300 spatial-temporal urban data sets which shows that our approach is scalable and effective at identifying interesting relationships.

Connected through hyperedge HE-1 (induced by source paper "debugging machine learning pipelines"):
  with members:
    - "macrobase prioritizing attention in fast data"
    - "qfix diagnosing errors through query histories"
    - "programing implementation of the quine mccluskey method for minimization of boolean expression"

Connected through hyperedge HE-2 (induced by source paper "amic an adaptive information theoretic method to identify multi scale temporal correlations in big time series data accepted version"):
  with members:
    - "fusing data with correlations"
    - "a mutual information approach to calculating nonlinearity"

Connected through hyperedge HE-3 (induced by source paper "progressive data science potential and challenges"):
  with members:
    - "a survey on deep learning toolkits and libraries for intelligent user interfaces"
    - "helix holistic optimization for accelerating iterative machine learning"
    - "progressive neural networks"
    - "generative adversarial active learning"
    - "enabling robots to communicate their objectives"
    - "progressive analytics a computation paradigm for exploratory data analysis"
    - "revisiting reuse in main memory database systems"
    - "an interactive machine learning framework"

Connected through hyperedge HE-4 (induced by source paper "vizrec a framework for secure data exploration via visual representation"):
  with members:
    - "bias in olap queries detection explanation and removal"
    - "controlling false discoveries during interactive data exploration"
    - "rapid sampling for visualizations with ordering guarantees"
    - "the vc dimension of queries and selectivity estimation through sampling"

Connected through hyperedge HE-5 (induced by source paper "idebench a benchmark for interactive data exploration"):
  with members:
    - "blinkdb queries with bounded errors and bounded response times on very large data"

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)