Abstract: An apparatus comprises a processing device configured to monitor traffic associated with a production application in a production environment of a software development platform, to generate software testing plans based on the monitored traffic, to identify software code to be tested for an updated version of the production application, and to select one or more of the software testing plans for testing the identified software code in a staging environment prior to integration testing in an integration testing environment of the software development platform. The processing device is also configured to perform the selected software testing plans on the identified software code in the staging environment, and to deploy the identified software code in the updated version of the production application in the integration testing environment based at on results of performing the selected software plans on the identified software code in the staging.

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: Disclosed embodiments provide a durable keyboard that provides haptic feedback and configurable surface display that is brightly lit. The keyboard includes microelectromechanical systems (MEMS) for generating the key surface displays, such as one or more MEMS lasers and software-controllable scanning mirrors. The keyboard also includes an optical medium, having for example beam splitters, optical waveguides, and lenses, to divide each projected image among a number of keys, and route each divided portion to the correct key for display. Finally, the key contact circuitry and depressible keys themselves are designed to be transparent or translucent, so the respective image is shown with high contrast on the pressable surface of each key.

Abstract: A method including 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 can 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 generating an approximate nearest neighbor index for the two sets of item embeddings. The method additionally can include receiving a basket including basket items selected by a user from the item catalog. The method further 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.

Abstract: A method including building a recommendation triggering model. The method can include receiving, via a user device of a user through a network, an add-to-cart command associated with an anchor item in a session by the user. The method further can include determining, in real-time after receiving the add-to-cart command, a recommendation for one or more complementary items based at least in part on: (a) the anchor item; and (b) a user profile of the user. The method also can include determining, in real-time after determining the recommendation, a recommendation confidence for the recommendation based at least in part on one or more of: (a) the user profile; (b) the anchor item; (c) the one or more complementary items; or (d) one or more feedbacks from the user associated with one or more prior recommendations in the session.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system stores a conversation containing a series of messages exchanged among a number of participants in a first document containing metadata for the conversation; a second document containing message content for the series of messages, wherein the message content includes a fixed position gap between starting or ending positions in consecutive messages in the series of messages; and one or more additional documents storing message metadata for individual messages in the conversation. Next, the system processes a first search across the series of messages in the conversation using an index of the set of documents. The system also processes, using the index, a second search within individual messages in the series of messages as a span query with a distance that is shorter than the fixed position gap.

Abstract: In one embodiment, a method includes, by one or more computing systems, receiving a user input comprising a plurality of n-grams from a user of a client system, generating a tree-structured representation for the user input based on a parsing by a compositional model, resolving the tree-structured representation by applying a depth-first search algorithm, wherein the tree-structured representation comprises one or more non-resolvable non-terminal nodes associated with one or more slots, and wherein each non-terminal parent node of a non-resolvable non-terminal node is partially resolved based on partial slot information associated with the non-resolvable non-terminal node, and wherein each non-resolvable non-terminal node is resolved based on the respective partially resolved non-terminal parent node of the non-resolvable non-terminal node, generating a response to the user input based on the resolved tree-structured representation, sending instructions for presenting the response to the client system of the

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving a user identifier, receiving an item identifier, determining user item quantity information related to quantities of the item previously selected by the user, determining a respective household size for each user, and determining aggregate household item quantity information related to quantities of the item previously selected by an aggregate of users of the same household size. If a first threshold level of the quantity of transactions is met, a recommended quantity is based on the user item quantity information, and if not, the recommended quantity is based on the aggregate household item quantity information. The user interface of the electronic device is updated to notify the user of the recommended quantity. Other embodiments are disclosed herein.

Abstract: A method including building a recommendation triggering model. The method can include receiving, via a user device of a user through a network, an add-to-cart command associated with an anchor item in a session by the user. The method further can include determining, in real-time after receiving the add-to-cart command, a recommendation for one or more complementary items based at least in part on: (a) the anchor item; and (b) a user profile of the user. The method also can include determining, in real-time after determining the recommendation, a recommendation confidence for the recommendation based at least in part on one or more of: (a) the user profile; (b) the anchor item; (c) the one or more complementary items; or (d) one or more feedbacks from the user associated with one or more prior recommendations in the session.

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: A method including 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 can 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 generating an approximate nearest neighbor index for the two sets of item embeddings. The method additionally can include receiving a basket including basket items selected by a user from the item catalog. The method further 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.

Abstract: A method, system and computer-usable medium are disclosed for executing a comparative analysis of microservice profiles and recommending modifications to a microservice. In at least one embodiment, a plurality of microservice analysis daemons and a plurality of microservices are deployed to nodes of a network. Run-time execution characteristic of the plurality of microservices are monitored and gathered by the analysis daemons for microservices executed at the node at which the microservice analysis daemon is deployed. Microservice profiles are generated using the run-time execution characteristics data and data retrieved from a service registry. Recommendations regarding modification of one or more microservices are made based on the results of a microservice profile comparative analysis.

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: Realized is a technique for estimating a state quantity of a vehicle, which technique is applicable to estimation of a vehicle weight and allows an increase in accuracy and speed of the estimation. A state quantity estimating device includes a data storing section (101), a predictive quantity computing section (102), an obtaining section (107), a Kalman gain computing section (103), an estimated quantity computing section (104) which calculates an estimated state quantity and estimated covariance, and a process noise covariance correcting section (106) which corrects process noise covariance. The estimated state quantity, the estimated covariance, and the process noise covariance, each of which has been calculated or corrected, are written in the data storing section (101) as a state quantity, state covariance, and process noise covariance, respectively, and are used in a next computation for estimating a state quantity.

Abstract: In some examples, a security application may monitor data received from one or more of sensors of a computing device, one or more input devices of the computing device, or one or more biometric sensors of a smartwatch that is connected to the computing device. If the user is not logged in and the user that is carrying the computing device has an uneven gait or is stumbling, the security app may, when the user initiates a login process, gather additional data, such as, from the sensors, the smartwatch, or both. If the user makes too many errors, based on data from the input devices, when attempting to login or after logging in, the security application may gather additional data. If the additional data indicates that the user may be under the influence of prescription or recreational drugs or alcohol, the user may be prevented from logging in.

Abstract: As an example, a computing device may broadcast, via a software application, a message to multiple computing devices requesting devices to participate in an activity occurring at a particular time at a particular location. A subset of the multiple computing devices may gather at the particular location prior to the particular time to participate in the activity. Prior to the particular time, the computing device may discover the subset and create a peer-to-peer network. Based on a set of attributes associated with each computing device in the subset, the computing device may assign individual computing devices in the subset a role and a position. Each of the computing devices in the subset may be positioned in the particular location according to the position and perform the role at the particular time to collectively perform the activity.

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 method includes retrieving information regarding a candidate from a plurality of sources, and analyzing the information regarding the candidate using one or more machine learning techniques. A plurality of questions for the candidate are generated based on the analysis. The method further includes receiving and analyzing a plurality of natural language responses to the plurality of questions from the candidate, and computing a plurality of confidence scores for the plurality of natural language responses using the one or more machine learning techniques. The plurality of questions and the plurality of confidence scores are provided to a user via a user interface.

Abstract: Disclosed embodiments provide a durable keyboard that provides haptic feedback and configurable surface display that is brightly lit. The keyboard includes microelectromechanical systems (MEMS) for generating the key surface displays, such as one or more MEMS lasers and software-controllable scanning mirrors. The keyboard also includes an optical medium, having for example beam splitters, optical waveguides, and lenses, to divide each projected image among a number of keys, and route each divided portion to the correct key for display. Finally, the key contact circuitry and depressible keys themselves are designed to be transparent or translucent, so the respective image is shown with high contrast on the pressable surface of each key.

Abstract: A system and method provide an interactive augmented reality experience customized for providing instant employee recognition in the workplace. A client electronic device streams camera image data to an instant recognition system. When the image includes a face, the system automatically identifies the imaged individual. The system then aggregates information about the individual from a variety of sources for transmission to the client electronic device for simultaneous display with the camera image. The system also may automatically generate a video of a person speaking about the individual using a generative adversarial network for streaming to the device in response to user activity. The system further may allow a user of the client electronic device to personalize the augmented reality experience by modifying or annotating the individual's face or body with amusing images using an interactive canvas.