公开(公告)号：US10092137B1

公开(公告)日：2018-10-09

申请号：US15087617

申请日：2016-03-31

Applicant: Amazon Technologies, Inc.

Inventor： Brent Stephen Nelson ,  Justine Lea Mahler ,  Agnes Gerner ,  Maciej Golonka ,  Jenna Lee Walsh ,  Brent William Lindberg

IPC: B65D25/04 ,  A47J41/00 ,  B65D81/38

Abstract: A thermal insulated delivery bag is configured for use with both hot and cold food delivery. The bag converts shape from a horizontal configuration to a vertical (tote) configuration which may optimize use depending on the type of food to be transported. For example, the horizontal configuration may accommodate large flat items while the vertical configuration may accommodate other items, which may be divided into separate internal sections by a divider. The bag includes a divider system to accommodate change in the size of two or more separate internal sections (e.g., segregating cold and hot items). The divider system enables movement/repositioning to change the size of the internal sections while maintaining a substantial thermal isolation of each internal section. In some embodiments, the divider may be held in a position/orientation by coupling of magnets to one or more ferrous strips in the bag.

公开(公告)号：US11030535B1

公开(公告)日：2021-06-08

申请号：US14749452

申请日：2015-06-24

Applicant: Amazon Technologies, Inc.

Inventor： Siddharth Arora ,  Maciej Golonka ,  Gustavo Eduardo Lopez ,  Dana Christopher LoPiccolo-Giles ,  Valerie Grace Millar

IPC: G06Q30/02 ,  G06N5/04 ,  G06N20/00

Abstract: Merchant quality may be inferred through machine learning techniques. A customer satisfaction classifier may receive data associated with a customer's engagement with a merchant, and may apply a machine learning model to the received data in order to infer a satisfaction of the customer with the merchant. The inferred satisfaction may be used to determine a rating of the merchant that is imputed to the customer.

公开(公告)号：US20180114242A1

公开(公告)日：2018-04-26

申请号：US14192420

申请日：2014-02-27

Applicant: Amazon Technologies, Inc.

Inventor： Gustavo Eduardo Lopez ,  Siddharth Arora ,  Maciej Golonka

IPC: G06Q30/02

CPC classification number: G06Q30/0224

Abstract: The systems and processes discussed herein may identify, prioritize, and recommend new deals to consumers based at least in part on triggering events. A consumer may interact with a previously acquired deal, such as by redeeming the deal, requesting a refund for the deal, etc. Such user interaction may be determined to be a triggering event. Based on a type of the triggering event, the systems described herein may identify one or more new deals having characteristics similar to the previously acquired deal. The one or more new deals may be recommended to a user at the same time or at some time after the triggering event occurs via a website, an e-mail message, an application associated with a user device, a text message, or any other manner that may be used to communicate the new deals to the user.