Abstract: Provided is a method, computer program product, and system for predicting a location of an object using machine learning. A processor may monitor a data stream received from one or more observation devices. The processor may detect a gesture initiated by a user from the data stream, the gesture indicating that the user is searching for an object. The processor may identify the object by analyzing a set of contextual data associated with the user. The processor may predict, in response to identifying the object, a location of the object by analyzing historic data associated with the object from the data stream. The processor may output the predicted location of the object to the user.

Abstract: Provided is a method, computer program product, and system for predicting a location of an object using machine learning. A processor may monitor a data stream received from one or more observation devices. The processor may detect a gesture initiated by a user from the data stream, the gesture indicating that the user is searching for an object. The processor may identify the object by analyzing a set of contextual data associated with the user. The processor may predict, in response to identifying the object, a location of the object by analyzing historic data associated with the object from the data stream. The processor may output the predicted location of the object to the user.

Abstract: As disclosed herein, an in-store feedback system permits shoppers to provide positive or negative feedback for a particular item using gestures or spoken language. To do so, the feedback system includes a gaze tracking module that identifies what product a shopper is currently focusing on. For example, a rack, which may contain multiple rows of shelves, is divided into a grid that includes a plurality of cells. By determining what cell the shopper is currently staring at, the gaze tracking system can identify a particular item by knowing which items are placed in which cell. The in-store feedback system may also include a gesture recognition system that identifies and decodes a gesture made by the shopper. For example, a thumbs up is positive feedback but a thumbs down is negative feedback. By recognizing the gesture, the gesture recognition system assigns positive or negative feedback to the item.

Abstract: Provided are a computer program product, system, and method for generating in a gaze tracking device augmented reality representations for objects in a user line-of-sight. A determination is made of user coordinates of a user position and coordinates of an axis of a line-of-sight of the user from the gaze tracking device. Requested object information is received indicating objects along the axis of the line-of-sight at different distances from the user position, including a first object in the line-of-sight that is visible to the user at a first distance from the user position and at least one additional object. Each of the at least one additional object is at a further distance from the user position than the first distance. Descriptions of the objects are rendered to the user in a view of the gaze tracking device along the axis of the line-of-sight.

Abstract: Embodiments provide techniques for creating and managing accumulator tables for use in generating reports for a business entity. Embodiments include identifying a report for a business entity. A plurality of data fields are determined across two or more database tables that are used to generate the report. Embodiments include creating an accumulator table and populating the accumulator table with data values for all of the plurality of data fields. Upon receiving, from a point of sale system, an indicator of an occurrence of a business event for the business entity, an instance of the report is automatically generated using the populated accumulator table.

Abstract: As disclosed herein, an in-store feedback system permits shoppers to provide positive or negative feedback for a particular item using gestures or spoken language. To do so, the feedback system includes a gaze tracking module that identifies what product a shopper is currently focusing on. For example, a rack, which may contain multiple rows of shelves, is divided into a grid that includes a plurality of cells. By determining what cell the shopper is currently staring at, the gaze tracking system can identify a particular item by knowing which items are placed in which cell. The in-store feedback system may also include a gesture recognition system that identifies and decodes a gesture made by the shopper. For example, a thumbs up is positive feedback but a thumbs down is negative feedback. By recognizing the gesture, the gesture recognition system assigns positive or negative feedback to the item.

Abstract: Systems and methods for advertising based on a context of use of a computing device are disclosed herein. According to an aspect, a method includes receiving advertisement content for presentation on a computing device. The method also includes determining a context of use of the computing device by a user. Further, the method includes determining supplemental content for presentation with the advertisement content based on the context of use. The method also includes presenting the advertisement content and the supplemental content via the computing device.

Abstract: Systems, methods, and computer program products to perform an operation comprising receiving selection of a food, determining a measure of similarity between the selected food and a plurality of taste preferences, wherein the measure of similarity is based at least in part on a plurality of taste attributes of the selected food, wherein each attribute of the plurality of taste attributes specifies a respective magnitude of a fundamental taste, of a plurality of fundamental tastes, and wherein each taste preference in the plurality of taste preferences specifies a respective preference for each fundamental taste, and upon determining that the measure of similarity is within a similarity threshold, displaying an indication that the selected food is preferable relative to the plurality of taste preferences.

Abstract: Embodiments provide techniques for creating and managing accumulator tables for use in generating reports for a business entity. Embodiments include identifying a report for a business entity. A plurality of data fields are determined across two or more database tables that are used to generate the report. Embodiments include creating an accumulator table and populating the accumulator table with data values for all of the plurality of data fields. Upon receiving, from a point of sale system, an indicator of an occurrence of a business event for the business entity, an instance of the report is automatically generated using the populated accumulator table.