Abstract: Techniques and systems for adjusting multiple hierarchies for consistency within levels of the hierarchies, using an optimization-based approach that results in an accurate projection across dimensions and levels in hierarchies.

Abstract: Indications of interest can be automatically generated. For example, attributes of an item can be received. There can be little or no historical data for the item. Multiple time series associated with other items can also be received. A first set of classifiers can identify a subset of magnitude-pattern groups based on the attributes. A first ensemble methodology can select a final magnitude-pattern group for the item from among the subset of magnitude-pattern groups. A second set of classifiers can determine a subset of interest volumes based on the attributes. A second ensemble methodology can select a final interest volume for the item from among the subset of interest volumes. Interest data can be generated based on the final magnitude-pattern group and the final interest volume. The interest data can provide an initial indication of interest in the item over a future time period.

Abstract: The present disclosure relates to resolving over multiple hierarchies. Specifically, various techniques and systems are provided for adjusting multiple hierarchies for consistency within levels of the hierarchies, using an optimization-based approach that results in an accurate projection across dimensions and levels in hierarchies.