Clustering to forecast sparse time-series data

  title={Clustering to forecast sparse time-series data},
  author={Abhay Jha and Shubhankar Ray and Brian Seaman and Inderjit S. Dhillon},
  journal={2015 IEEE 31st International Conference on Data Engineering},
Forecasting accurately is essential to successful inventory planning in retail. Unfortunately, there is not always enough historical data to forecast items individually- this is particularly true in e-commerce where there is a long tail of low selling items, and items are introduced and phased out quite frequently, unlike physical stores. In such scenarios, it is preferable to forecast items in well-designed groups of similar items, so that data for different items can be pooled together to fit… CONTINUE READING


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