Predicting "What is Interesting" by Mining Interactive-Data-Analysis Session Logs

@inproceedings{Somech2019PredictingI,
  title={Predicting "What is Interesting" by Mining Interactive-Data-Analysis Session Logs},
  author={Amit Somech and Tova Milo and Chai Ozeri},
  booktitle={EDBT},
  year={2019}
}
Assessing the interestingness of data analysis actions has been the subject of extensive previous work, and a multitude of interestingness measures have been devised, each capturing a different facet of the broad concept. While such measures are a core component in many analysis platforms (e.g., for ranking association rules, recommending visualizations, and query formulation), choosing the most adequate measure for a specific analysis task or an application domain is known to be a difficult… CONTINUE READING

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