Abstract: At least one embodiment of the disclosed system is directed to a computer-implemented method for operating a light projection technology keyboard of an Information Handling System. The computer-implemented method may include receiving electronic environmental condition data at a keyboard configuration system, and processing the electronic environmental condition data through a neural network of an adaptive configuration engine. The neural network may output one or more functions and/or visual settings to be used in configuring operation of the light projection technology keyboard. The light projection technology keyboard may be controlled based on the one or more functions and/or visual settings output by the neural network. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

Abstract: Methods, apparatus, and processor-readable storage media for generating context-based question-answer pairs by applying artificial intelligence techniques to context-related data are provided herein.

Abstract: Methods, systems, and computer program products for selection of a witness during virtualization system recovery after a disaster event. A recovery plan is configured to identify a witness that is then used to elect a leader to implement the recovery. Various system, and/or network, and/or component failures and/or various loss of function of components of the virtualization system can trigger initiation of the recovery plan. Based on the particular recovery plan that is invoked upon a determination of a network outage, or component failure or loss of function of a component of the virtualization system, a particular witness corresponding to a subset of entities of the particular recovery plan is selected. The witness is used to elect the leader, and the leader initiates actions of the recovery plan. The implementation of the recovery plan includes consideration of the health of components that would potentially be involved in the recovery actions.

Abstract: This application relates to apparatus and methods for automatically determining and providing personalized digital recommendations including sponsored items. In some examples, a computing device receives a recommendation request. In response, the computing device determines an initial set of items for recommendation based on a relevance of associated items to the user and potential revenue from user interactions with the associated items. The computing device then generates final item recommendations by replacing at least one item of the initial set of items with a closest sponsored item that is selected based on a similarity of the closest sponsored item to the corresponding item. The final item recommendations are then presented to the user.

Abstract: This application relates to apparatus and methods for automatically determining item relevancy based on textual information. In some examples, a computing device receives a search query, and a plurality of items corresponding to the search query. The computing device may identify one or more features of the search query. The computing device may generate relevancy values for each of the items based on the features of the search query, and features of each of the plurality of items. For example, the computing device may generate, for each of the items, a plurality of relevance values, each relevance value generated based on a feature of the search query and corresponding features of the item. The computing device may transmit the generated relevancy values for the plurality of items. In some examples, the computing device may rank the plurality of items based on the generated relevancy values.

Abstract: This application relates to apparatus and methods for providing recommended items to advertise. In some examples, a computing device determines a first set of items for recommendation based on historical user data associated with a user, and a second set of items for recommendation based on real-time user session data for the user. The computing device may then determine a subset of the first set of items based on associated scores and a predetermined threshold number of first items that can be presented for optimal user interaction. The computing device may generate a set of item recommendations by combining the subset of the first set of items and at least one of the second set of items to present to the user as advertisements.

Abstract: Systems and methods for prioritizing enhancement and/or improvements of features of a user application are disclosed. In at least one embodiment, a method includes retrieving analytics data generated by an analytics engine, where the analytics data includes data relating to user interactions with a feature of the user application. A plurality of vectors is generated from the analytics data. The plurality of vectors include vectors corresponding to user interactions with the feature. A priority is assigned to enhancing and/or improving the feature of the user application based on a weighted sum of the plurality of vectors.

Abstract: As an example, a server hosting a search engine may receive a search query and determine a searched time interval, a searched object, and a searched event. The server may select, based on the searched time interval, a portion of an object-event bipartite graph that was created using information gathered from social media sites. The server may compare attributes of individual events in the portion with attributes of the searched event to identify a set of relevant events. The server may determine objects associated with the relevant events and compare attributes of individual objects with the attributes of the searched object to identify a set of relevant objects. The search engine may provide search results that include the set of relevant objects ordered according to their similarity to the searched object.

Abstract: The present disclosure provides the planning of the next generation network which complements an existing telecom deployment to achieve the desired KPIs from the combined network for both macro and small cell planning in an existing network in a cost-effective method to deploy ODSC cells and Macro Cells in a heterogeneous network. Planning a next-generation network for an existing telecom operator is a large undertaking, utilizing precious man-hours and most importantly, weeks of work. Using an automated planning methodology to plan macro and small cells for a region like a city, state or even country, planners can deploy solutions to make the most optimum use of existing infrastructure. The invention proposes an automated approach to plan the preferred overlay telecom solutions in an area A being part of an existing telecom deployment.

Abstract: A system and method automatically refactor mature program code having interdependent features to remove instructions pertaining to features that are no longer used. To facilitate reduction of the number of feature dependencies to test, instrumentation data are analyzed to determine which of the available features are in actual use. A graph of feature dependencies is built based on the program configuration, and the program code is simulated, according to existing testing protocols, with various combinations of features disabled to determine whether the program continues to function without error. When features are found that can be safely removed, the codebase is automatically refactored to eliminate the implementing code corresponding to the features. The refactored code then may be further automatically retested and deployed into the production environment.

Abstract: A system of one or more computers that are configured to generate documentation for microservice-based applications is disclosed. In at least one embodiment, usage information relating to actual usage by one or more users of a plurality of microservices, features extracted from user story information in a backlog tracker, and a call-context graph including information identifying calling functions and called functions in the plurality of microservices are used to generate data that is provided to a natural language generator, which uses the information to automatically generate documentation for the microservice based application.

Abstract: This application relates to apparatus and methods for automatically determining and providing carousels specifically curated for a user. In some examples, a computing device obtains user transaction data identifying in-store and/or online transactions, and user engagement data identifying user interactions with items and carousels from user's prior sessions. The computing device determines a sequential order for presentation of carousels with a set of item recommendations. For example, the computing device scores each potential carousel based on prior user interactions and transactions with items and carousels. The carousels are then ranked and subsequently presented to the user based on their corresponding scores.

Abstract: A method including receiving a basket including basket items selected by a user from an item catalog. The method also can include grouping the basket items of the basket into categories based on a respective item category of each of the basket items. The method additionally can include randomly sampling a respective anchor item from each of the categories. The method further can include generating a respective list of complementary items for the respective anchor item for the each of the categories based on a respective score for each of the complementary items generated using two sets of trained item embeddings for items in the item catalog and using trained user embeddings for the user. The two sets of trained item embeddings and the trained user embeddings can be trained using a triple embeddings model with triplets.

Abstract: Approaches are described for ranking images against image effects. An image effect is identified from a plurality of image effects. Each image effect includes instructions defining steps of modifying visual data of an input image to produce an output image. Preview images are generated, where for each data object of a plurality of data objects the instructions of the image effect are applied to a respective image corresponding to the data object to generate a preview image of the data object. Ranking scores are determined, where for each data object visual data of the respective image is analyzed using a set of evaluation criteria associated with the image effect to determine a ranking score of the image effect for the data object. Data is transmitted which causes at least one of the preview images to be presented on a user device based on the ranking scores.

Abstract: An apparatus comprises a processing device configured to select a given notification to be delivered from a first computing device to a second computing device and to determine (i) first notification metrics associated with one or more previous notifications delivered to a set of one or more computing devices including the second computing device and (ii) second notification metrics associated with a current status of the second computing device. The processing device is also configured to provide the first and second notification metrics to one or more machine learning models, to identify recommendations for modifying delivery of the given notification from the first computing device to the second computing device based on output of the one or more machine learning models, and to modify the delivery of the given notification from the first computing device to the second computing device based on the identified recommendations.

Abstract: In some examples, a server may determine a browsing history associated with a user, identify activities associated with purchasing a device, and determine features of the device. Individual features may be assigned a corresponding priority based on the browsing history. A machine learning algorithm may predict a configuration of the device based on the features and the corresponding priorities. The server may create a web page that describes a specification of the device based on the configuration and includes a comparison of at least some of the features of the device with other features of similar devices. The server may send a notification with a link to the web page. The web page may enable the user to modify the configuration and modify a price of the device. The server may receive a purchase order to purchase the device and instruct a manufacturing facility to build-to-order the device.

Abstract: At least one embodiment of the disclosed system is directed to a computer-implemented method for operating a light projection technology keyboard of an Information Handling System. The computer-implemented method may include receiving electronic environmental condition data at a keyboard configuration system, and processing the electronic environmental condition data through a neural network of an adaptive configuration engine. The neural network may output one or more functions and/or visual settings to be used in configuring operation of the light projection technology keyboard. The light projection technology keyboard may be controlled based on the one or more functions and/or visual settings output by the neural network. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

Abstract: A method being implemented via execution of computing instructions configured to run at one or more processors and stored at one or more non-transitory computer-readable media. The method can include training two sets of item embeddings for items in an item catalog and a set of user embeddings for users, using a triple embeddings model, with triplets. The triplets each include a respective first user of the users, a respective first item from the item catalog, and a respective second item from the item catalog, in which the respective first user selected the respective first item and the respective second item in a respective same basket. The method also can include randomly sampling an anchor item from a category of items selected by a user. The method additionally can include generating a list of complementary items using a query vector associated with the user and the anchor item.

Abstract: An apparatus comprises at least one processing device configured to perform steps of receiving a request to determine a path to a given web element of a web page of a web application and parsing the web page to detect web elements of the web page including the given web element and one or more additional web elements. The at least one processing device is also configured to perform steps of identifying one or more of the additional web elements having designated characteristics and selecting one of the identified web elements based at least in part on locations of the identified web elements, relative to the given web element, in a tree structure of the web page. The at least one processing device is further configured to perform the step of determining the path to the given web element from the selected web element.

Abstract: A system and method include migrating, by a migration controller, a first entity of a first subset of entities from a source site to a target site in a virtual computing system based on an asynchronous mode of replication. The system and method also include replicating, by the migration controller, data of a second entity of a second subset of entities from the source site to the target site based on a synchronous mode of replication in parallel with the migration of the first entity for dynamically adjusting a recovery time objective parameter.