公开(公告)号：US20170068484A1

公开(公告)日：2017-03-09

申请号：US15257545

申请日：2016-09-06

Applicant: SAS Institute Inc.

Inventor： KEVIN L. SCOTT ,  METIN BALIKCIOGLU ,  BINGFENG DING ,  SHENGKUEI LIN ,  TUGRUL SANLI

IPC: G06F3/06

CPC classification number: G06Q10/0631 ,  G06Q10/02 ,  G06Q10/06 ,  G06Q10/06312 ,  G06Q30/0202 ,  G06Q50/12 ,  H04L47/782 ,  H04L47/823

Abstract: Exemplary embodiments are generally directed to methods, mediums, and systems for correcting censored or constrained historical data with various possible types of computing devices, including cloud-based devices, personal computing devices, and edge-based devices. The corrected data may be used in forecasting, for example to forecast demand for a limited resource. In some embodiments, the data is modeled at a higher level of granularity than an individual record. The aggregated demand may then be pro-rated over a group of categories or users where a given category of users that might be small or nonexistent over a certain time frame may be better accommodated. Moreover, it may be easier or more efficient to make assumptions and employ computing resources at the aggregate level.

Abstract translation: 示例性实施例通常涉及用于使用各种可能类型的计算设备（包括基于云的设备，个人计算设备和基于边缘的设备）来校正被检查或约束的历史数据的方法，介质和系统。 校正的数据可用于预测，例如用于预测有限资源的需求。 在一些实施例中，数据以比单个记录更高的粒度级进行建模。 然后可以对一组类别或用户评估总需求，其中在某一时间范围内可能小或不存在的给定类别的用户可能更好地适应。 此外，在总体水平上进行假设和采用计算资源可能更容易或更有效。