QSAnglyzer: Visual Analytics for Prismatic Analysis of Question Answering System Evaluations

@article{Chen2017QSAnglyzerVA,
  title={QSAnglyzer: Visual Analytics for Prismatic Analysis of Question Answering System Evaluations},
  author={Nan-Chen Chen and Been Kim},
  journal={2017 IEEE Conference on Visual Analytics Science and Technology (VAST)},
  year={2017},
  pages={48-58}
}
Developing sophisticated artificial intelligence (AI) systems requires AI researchers to experiment with different designs and analyze results from evaluations (we refer this task as evaluation analysis). In this paper, we tackle the challenges of evaluation analysis in the domain of question-answering (QA) systems. Through in-depth studies with QA researchers, we identify tasks and goals of evaluation analysis and derive a set of design rationales, based on which we propose a novel approach… CONTINUE READING

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