Target Brands, Inc.

Amit Pande

Kai Ni

Jacob Portnoy

Jesse Berwald

Ryan David Siskind

Sayon Majumdar

Satyajit Vishram Gupte

Vishal Ahuja

Brian Copeland

Sarasadat Amini

Rahul Biswas

Aparupa Das Gupta

Methods and systems for optimizing a product assortment, and managing product fulfillment, are disclosed. One method includes utilizing a model trained on item data to identify item substitution pairs within an item category of an item assortment, the item substitution pairs being identified as having a substitutability score above a predetermined threshold. The method further includes applying an assortment optimization model to generate an assortment recommendation for the item category at an identified retail location. A request for an item not included in the assortment recommendation may result in suggestion of an identified substitutable item from among the item substitution pairs.

Item substitution techniques for assortment optimization and product fulfillment

Methods and systems for providing a digital cart management system for use by customers within a retail location. In use, a customer shops within a retail location and adds items to a digital cart as the customer is adding the items to a physical cart, e.g., at least in part by voice input. When the customer is finished shopping, the customer can checkout via a digital process, thereby bypassing point of sale devices at the retail location.

Voice-based in-store digital checkout system

Methods and systems for generating item recommendations are disclosed. One method includes sampling from a weighted node-based graph to generate a sampled graph, wherein sampling includes selecting a plurality of nodes and, for each selected node, one or more node pairs. The selection of the node pairs is based at least in part based on a weight assigned to the node pair in the weighted node-based graph. The method further includes aggregating information from the one or more neighboring nodes into each corresponding node of the plurality of nodes in the sampled graph to generate a vector representation of the sampled graph. The method also includes applying a loss function to the vector representation of the sampled graph to generate a modified vector representation. The modified vector representation is used to generate, in response to identification of an item from an item collection, a selection of one or more recommended items from within the item collection.

Item recommendations using convolutions on weighted graphs

Methods and systems for predicting relevant items to be presented to a user in an online environment are described. The methods and systems described herein generate models based on previous item selections to determine an overall time series model for predicting a relevant time of next item selection as well as items most likely to be selected at that time. Complementary items can be presented to the user alongside the selection of most relevant items.

Method and system for presenting items in online environment based on previous item selections

Methods and systems for generating and presenting item recommendations to a user at a retail website is disclosed. One method includes generating a set of item recommendations based on a selected item from a retail website. The method also includes identifying one or more facets in the set of item recommendations, and, for each of the one or more facets, identifying a subset of items from the set of item recommendations affiliated with the facet. The method also includes generating a user interface including the selected item and a recommendation region displaying at least some of the subset of items affiliated with the facet.

Faceted item recommendation system

Methods and systems for authenticating and continuously re-authenticating users are disclosed. Most software applications executing on mobile devices only require a user to provide identification information (e.g., user ID and password) at the outset of launching the application, and infrequently or never subsequently request user identification information. The methods and systems described herein provide continuous protection of user identities using a combination of touch-based biometric sensor data, motion sensor data, and implicit mobile device data.

Continuous guest re-authentication system

Aspects of the present disclosure describe systems and methods for rapidly detecting threats or other security breaches in enterprise networks. In particular, all enterprise network communications may be monitored to detect anomalous events. In one example, each event log in a collection of event logs may be evaluated, wherein an event log having one or more features is monitored and identified as being anomalous based on identifying one or more anomalous features therein. Anomalous features are identified as being anomalous based on the existence of one or more features in the event log that deviate from characteristic contextual features. Rules or models may thereafter applied to each event log containing the anomalous feature.

Growing community of inventors

Ames, IA, United States of America

Amit Pande