Amazon Technologies, Inc.

James Joseph Jesensky

Isaac W Oates

Steve Huynh

Vinay P Vaidya

Samuel Scott Gigliotti

Ronald Alan Morris

Tracy Dianne Schultz

Angela Lam

Raghav Kishor Phadke

Anil Kumar Kalagatla

Jean Sevak Froundjian

Ari Liberman Garcia

Leon Amdour

Amit D Agarwal

Leo Parker Dirac

Nicolle M Correa

Robert Matthias Steele

Tianming Zheng

Vinaiy Vaidya

Systems, methods, and computer-readable media are disclosed for generating personalized and contextually relevant cards and delivering the cards to card clients for presentation to a user.

Contextual card generation and delivery

A request to split a data set comprising observation records located in a group of storage objects is received. With respect to a particular observation record, a token is generated based on an identifier of the record's storage object and a key value of the record. A numeric value is calculated using the token, and the observation record is assigned to a split subset using the numeric value. An indication of the assignment is provided to a destination associated with the split subset.

Consistent randomized record-level splitting of machine learning data

Systems, methods, and computer-readable media are disclosed for generating cards that include personalized content that is relevant to tastes or preferences of a user and contextually relevant to a current, historical, or future use context of a user device. The card content is determined to be relevant to a current use context of a user device based on an evaluation of contextual data with respect to constraints associated with the card. The card content is transmitted to a card client for presentation via a user interface of the client when the card content is deemed relevant to the current use context of the device.

Techniques for automatically approving transactions are described herein. These techniques may include determining whether a user who requested to conduct a transaction is the same user as a user that approves the transaction. If so, then the transaction may be approved. If not, then the approving user may be asked to provide authentication information in order to finish the approval process.

Automatic approval

Techniques for generating and providing phrases are described herein. These techniques may include analyzing one or more sources to generate a first corpus of phrases, each of the phrases for use as an identifier and/or for association with a user. Once a first corpus of phrases has been generated, these phrases may be filtered to define a second corpus of phrases. Phrases of this second corpus may then be suggested to one or more users. In some instances, the phrases suggested to a particular user are personalized to the user based on information previously known about the user or based on information provided by the user.

Generating constructed phrases

Techniques for determining phrases that are related or similar to a source phrase are described herein. These techniques may include analyzing a corpus of text to locate a first set of phrases that differ from a received source phrase by one word. The techniques may then combine these words of the first set of phrases that differ from the source phrase to create a second set of phrases. The techniques may then filter out a portion of the second set of phrases before outputting another portion for use as an identifier, for association with a user account or for any other use.

Determining similar phrases

Techniques for generating and providing phrases are described herein. These techniques may include analyzing one or more sources to generate a statistically improbable phrase, determining words that compose the statistically improbable phrase, inputting the words into an index, and determine phrases associated with the words. The determined phrases may then be presented to a user.

Determining phrases related to other phrases

Techniques for generating and providing phrases are described herein. These techniques may include analyzing one or more sources to generate a first corpus of phrases, each of the phrases for use as an identifier and/or for association with a user for executing a transaction. Once a first corpus of phrases has been generated, these phrases may be filtered to define a second corpus of phrases. Phrases of this second corpus may then be suggested to one or more users. In some instances, the phrases suggested to a particular user are personalized to the user based on information previously known about the user or based on information provided by the user.

Generating and suggesting phrases

Mining phrases for association with a user

Techniques for generating and providing phrases are described herein. These techniques may include analyzing one or more sources to generate a first corpus of phrases, each of the phrases for use as an identifier and/or for association with a user. The first corpus of phrases may be generated based on characteristics associated with phrases. Once a first corpus of phrases has been generated, these phrases may be filtered to define a second corpus of phrases. Phrases of this second corpus may then be suggested to one or more users. In some instances, the phrases suggested to a particular user are personalized to the user based on information previously known about the user or based on information provided by the user.

Growing community of inventors

Issaquah, WA, United States of America

James Joseph Jesensky