Abstract: Systems and methods for providing a food product recommendation are disclosed. A computer-implemented method includes: determining, by a computing device, that a user with a mobile device enters a store; obtaining, by the computing device, user data that is based on wearable health data, taste data, and preference data of the user; obtaining, by the computing device, store data for plural food products; determining, by the computing device, a recommended food product from the plural food products based on comparing the user data to the store data; and providing, by the computing device, an indication of the recommended one of the plural food products for display on the mobile device of the user. The user data may be that of a single user or plural users, such as a family.

Abstract: A method, apparatus, system, and computer program product for configuring an image capture device. A target activity context for a target object in an image is received by a computer system from the image capture device. A set of photographers for the target object is identified using target activity context. The set of photographers identified is sent to the image capture device. Responsive to receiving a selection of a photographer from the set of photographers from the image capture device, an inbound activity context for the photographer for the target object is sent to the image capture device, wherein the image capture device is configured to capture the image of the target object using the inbound activity context.

Abstract: The method includes receiving a location of a client device and one or more items of interest to a user of the client device. The method further includes determining that the location of the client device is within a threshold distance of an item of the one or more items of interest. The method further includes generating a communication with the user of the client device. The method further includes receiving a response from the user of the client device. The method further includes determining if the received response indicates an intent to purchase the item. In one embodiment, the method further includes identifying a sales representative to assist the user of the client device, responsive to determining that the received response indicates an intent to purchase the item.

Abstract: The method includes receiving a location of a client device and one or more items of interest to a user of the client device. The method further includes determining that the location of the client device is within a threshold distance of an item of the one or more items of interest. The method further includes generating a communication with the user of the client device. The method further includes receiving a response from the user of the client device. The method further includes determining if the received response indicates an intent to purchase the item. In one embodiment, the method further includes identifying a sales representative to assist the user of the client device, responsive to determining that the received response indicates an intent to purchase the item.

Abstract: A method, computer program product, and visual display apparatus include a processor(s) obtaining data indicating that a user wearing the apparatus (which included an image capture device, and a projection device, communicatively coupled to the processor(s)), perceives displayed text with consistent character differences. The processor(s) obtains, from the image capture device, an image of a visual display within a visual range of the image capture device; the image includes textual elements. Based on the data, the processor(s) transforms the image into the new image that includes the textual elements with pre-defined character substitutions, based on the consistent character differences. The processor(s) displays, via the projection device, the new image, to the user, wherein based on viewing the new image, the user views the textual elements without the consistent character differences.

Abstract: The method includes receiving a location of a client device and one or more items of interest to a user of the client device. The method further includes determining that the location of the client device is within a threshold distance of an item of the one or more items of interest. The method further includes generating a communication with the user of the client device. The method further includes receiving a response from the user of the client device. The method further includes determining if the received response indicates an intent to purchase the item. In one embodiment, the method further includes identifying a sales representative to assist the user of the client device, responsive to determining that the received response indicates an intent to purchase the item.

Abstract: Character input error correction is provided by receiving from a keyboard character input by a user. The character input includes character input errors by the user, the character input errors being input of incorrect characters by the user via the keyboard. The character input errors of the character input are automatically identified and classified into character error classification(s). Each character error classification corresponds to a respective visual transformation of input characters. It is determined that a frequency of the identified and classified character input errors exceeds a predefined threshold confidence level for triggering application of keyboard corrections for user input. Based on the determining, keyboard corrections are applied for user input. The applying keyboard corrections includes applying a correction to character(s) displayed for or input by the user. The applied correction is based on at least one of the classification(s) into which the character input errors are classified.

Abstract: A computer system monitors a user to assess product preferences. A video from an image capture device monitoring a user is analyzed. An image is selected from the video of the user for image processing, wherein the user is visible in the frame. The selected image is processed to determine one or more products used by the user. One or more product recommendations are determined based on the one or more products used by the user. Embodiments of the present invention further include a method and program product for assessing product preferences for a user in substantially the same manner described above.

Abstract: A computer system monitors a user to assess product preferences. A video from an image capture device monitoring a user is analyzed. An image is selected from the video of the user for image processing, wherein the user is visible in the frame. The selected image is processed to determine one or more products used by the user. One or more product recommendations are determined based on the one or more products used by the user. Embodiments of the present invention further include a method and program product for assessing product preferences for a user in substantially the same manner described above.

Abstract: Character input error correction is provided by receiving from a keyboard character input by a user. The character input includes character input errors by the user, the character input errors being input of incorrect characters by the user via the keyboard. The character input errors of the character input are automatically identified and classified into character error classification(s). Each character error classification corresponds to a respective visual transformation of input characters. It is determined that a frequency of the identified and classified character input errors exceeds a predefined threshold confidence level for triggering application of keyboard corrections for user input. Based on the determining, keyboard corrections are applied for user input. The applying keyboard corrections includes applying a correction to character(s) displayed for or input by the user. The applied correction is based on at least one of the classification(s) into which the character input errors are classified.

Abstract: A method, computer program product, and visual display apparatus include a processor(s) obtaining data indicating that a user wearing the apparatus (which included an image capture device, and a projection device, communicatively coupled to the processor(s)), perceives displayed text with consistent character differences. The processor(s) obtains, from the image capture device, an image of a visual display within a visual range of the image capture device; the image includes textual elements. Based on the data, the processor(s) transforms the image into the new image that includes the textual elements with pre-defined character substitutions, based on the consistent character differences. The processor(s) displays, via the projection device, the new image, to the user, wherein based on viewing the new image, the user views the textual elements without the consistent character differences.

Abstract: Character input error correction is provided by receiving from a keyboard character input by a user. The character input includes character input errors by the user, the character input errors being input of incorrect characters by the user via the keyboard. The character input errors of the character input are automatically identified and classified into character error classification(s). Each character error classification corresponds to a respective visual transformation of input characters. It is determined that a frequency of the identified and classified character input errors exceeds a predefined threshold confidence level for triggering application of keyboard corrections for user input. Based on the determining, keyboard corrections are applied for user input. The applying keyboard corrections includes applying a correction to character(s) displayed for or input by the user. The applied correction is based on at least one of the classification(s) into which the character input errors are classified.

Abstract: Generating recommendations for an individual based on a mood of the individual. Receiving information corresponding to one or more activities associated with an individual over a period of time. The received information corresponding to the one or more activities associated with the individual is processed to detect a mood of the individual. A recommendation is generated for the individual based on the detected mood of the individual and a future event associated with the individual. The future event has an occurrence at a later time instance.

Abstract: According to an embodiment of the present invention, a system dynamically captures and stores an image based on the context of the image being captured. Initially, an image capture device receives and analyzes an image to determine a first set of one or more attributes associated with the image. A processor compares the first set of attributes associated with the image with a second set of one or more pre-defined attributes associated with an image context indicating preferences for image capture, and, based on the results of the comparing, instructs the image capture device to store the image. Embodiments of the present invention further include a method and computer program product for capturing an image based on the context of the image in substantially the same manner described above.

Abstract: A method, computer program product, and system for generating flavor profile models are provided. An alpha flavor model is determined. An electrode signal is transmitted to a taste simulator based on the alpha flavor model. User feedback is received. A variance between the alpha flavor model and the user feedback is determined. The variance is compared to a predetermined threshold. In response to determining that the variance is greater than the predetermined threshold, a beta flavor model is generated.

Abstract: A method, computer program product, and system for generating flavor profile models are provided. An alpha flavor model is determined. An electrode signal is transmitted to a taste simulator based on the alpha flavor model. User feedback is received. A variance between the alpha flavor model and the user feedback is determined. The variance is compared to a predetermined threshold. In response to determining that the variance is greater than the predetermined threshold, a beta flavor model is generated.

Abstract: According to an embodiment of the present invention, a system dynamically captures and stores an image based on the context of the image being captured. Initially, an image capture device receives and analyzes an image to determine a first set of one or more attributes associated with the image. A processor compares the first set of attributes associated with the image with a second set of one or more pre-defined attributes associated with an image context indicating preferences for image capture, and, based on the results of the comparing, instructs the image capture device to store the image. Embodiments of the present invention further include a method and computer program product for capturing an image based on the context of the image in substantially the same manner described above.

Abstract: A computer-implemented method comprising: presenting, by a computing device, an advertisement on a first device; monitoring, by the computing device, viewing activity by a user of the advertisement, wherein the monitoring comprises tracking an amount of time that the user actively views the advertisement on the first device; and continuing, by the computing device, playback of the advertisement on one or more second devices until the user has actively viewed the advertisement for a target impression time based on the monitoring.

Abstract: Systems and methods for determining advertisement content based on cluster density analysis of advertisement targets within a dynamic visibility fence are disclosed. A computer-implemented method includes determining, by an advertisement determination device, a dynamic visibility fence for a time, the dynamic visibility fence defining a first set of advertisement targets, determining, by the advertisement determination device, an advertisement to display based on cluster analysis of the first set of advertisement targets, and displaying, by the advertisement determination device, the determined advertisement.

Abstract: Systems and methods for providing a food product recommendation are disclosed. A computer-implemented method includes: determining, by a computing device, that a user with a mobile device enters a store; obtaining, by the computing device, user data that is based on wearable health data, taste data, and preference data of the user; obtaining, by the computing device, store data for plural food products; determining, by the computing device, a recommended food product from the plural food products based on comparing the user data to the store data; and providing, by the computing device, an indication of the recommended one of the plural food products for display on the mobile device of the user. The user data may be that of a single user or plural users, such as a family.