human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "viznet towards a large scale visualization learning and benchmarking repository"):
  Abstract: Researchers currently rely on ad hoc datasets to train automated visualization tools and evaluate the effectiveness of visualization designs. These exemplars often lack the characteristics of real-world datasets, and their one-off nature makes it difficult to compare different techniques. In this paper, we present VizNet: a large-scale corpus of over 31 million datasets compiled from open data repositories and online visualization galleries. On average, these datasets comprise 17 records over 3 dimensions and across the corpus, we find 51% of the dimensions record categorical data, 44% quantitative, and only 5% temporal. VizNet provides the necessary common baseline for comparing visualization design techniques, and developing benchmark models and algorithms for automating visual analysis. To demonstrate VizNet's utility as a platform for conducting online crowdsourced experiments at scale, we replicate a prior study assessing the influence of user task and data distribution on visual encoding effectiveness, and extend it by considering an additional task: outlier detection. To contend with running such studies at scale, we demonstrate how a metric of perceptual effectiveness can be learned from experimental results, and show its predictive power across test datasets.

Includes members:
  Member "idebench a benchmark for interactive data exploration":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sample debiasing in the themis open world database system extended version")
  Member "beyond heuristics learning visualization design":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "data2vis automatic generation of data visualizations using sequence to sequence recurrent neural networks")
  Member "vizml a machine learning approach to visualization recommendation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "towards automated infographic design deep learning based auto extraction of extensible timeline")
  Member "data2vis automatic generation of data visualizations using sequence to sequence recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards automated infographic design deep learning based auto extraction of extensible timeline")
  Member "task based effectiveness of basic visualizations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "juxtaposing controlled empirical studies in visualization with topic developments in psychology")
  Member "beagle automated extraction and interpretation of visualizations from the web":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "leaf qa locate encode attend for figure question answering")
  Member "squad 100 000 questions for machine comprehension of text":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "bert can see out of the box on the cross modal transferability of text representations")
  Member "boomerang rebounding the consequences of reputation feedback on crowdsourcing platforms":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "designing optimal binary rating systems")

Question: Please tell me which class the source paper 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.HC(Human-Computer Interaction)