Abstract: A method for forming at least one microservice is provided. The method includes the steps of getting a monolith application to disintegrate, scanning codes of the monolith application, finding one or more nanoservice candidates in the codes, and recommending at least one microservice to a user. Herein, the at least one microservice is a group of one or more selected nanoservice candidates sharing a common characteristic. According to an input of the user, at least one microservice selected among the at least one recommended microservice is generated.

Abstract: Methods, apparatus, and processor-readable storage media for autonomous creation of new microservices and modification of existing microservices are provided herein. An example computer-implemented method includes generating and outputting, to a user via at least one graphical user interface, one or more prompts for user input pertaining to a target microservice; automatically configuring, for the target microservice, one or more microservice components based at least in part on the user input received in response to the one or more prompts; building the target microservice based at least in part on the one or more automatically configured microservice components; and outputting the built target microservice to at least one of a user and one or more cloud platforms.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system retrieves, from a nearline data store, one or more updates representing recent activity for a member of an online network. Next, the system performs one or more queries using data in the updates to identify a set of candidates for recommending to the member. The system then applies one or more machine learning models to features for the set of candidates to generate a ranking of the set of candidates and updates the ranking based on additional features for an additional set of candidates from an offline data store. Finally, the system outputs, to the member, at least a portion of the updated ranking as connection recommendations in the online network.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system stores a set of feed updates associated with a set of entities in descending chronological order within a set of resizable blocks. For each entity in the set of entities, the system generates an index containing one or more lists of resizable blocks storing a subset of the feed updates associated with the entity, wherein the one or more lists are sorted in descending chronological order. The system then uses the index to generate a content feed containing a selection of the feed updates for outputting to a viewer.

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: Techniques for enhancing usability and electronic resource efficiency using comment relevance are disclosed herein. In some embodiments, a comment relevance system receives member feature data, including professional identity data such as professional experience or professional skill, and at least one of comment feature data and commenter feature data for comments for post on a social networking service, generates a score for each comment based on the member feature data and the comment or commenter feature data, ranks the comments based on the scores, and causes one or more of the comments to be displayed in a particular position based on the ranking. In some embodiments, the member feature data comprises professional identity data of a member of the social networking service, the comment feature data indicates at least one attribute of the comment, and the commenter feature data indicates at least one attribute of the commenter of the comment.

Abstract: A system and method for stemming flow of information from a negative campaign are described. A status for each node of a set of preselected nodes in a social network graph is identified. The status indicates whether a node has been infected with information from a negative campaign. A source and a flow of the negative campaign are identified based on the status of the nodes from the set of preselected nodes and a topology of the social network graph. A susceptibility score is computed for one or more nodes of the social network. The susceptibility score is computed using a measure of vulnerability of nodes that have not received the information based on the flow of the negative campaign, and a measure of reachability of nodes from the source. Nodes susceptible to adopting and spreading the information from the negative campaign are identified based on the susceptibility score.

Abstract: A system and method for stemming flow of information from a negative campaign are described. A status for each node of a set of preselected nodes in a social network graph is identified. The status indicates whether a node has been infected with information from a negative campaign. A source and a flow of the negative campaign are identified based on the status of the nodes from the set of preselected nodes and a topology of the social network graph. A susceptibility score is computed for one or more nodes of the social network. The susceptibility score is computed using a measure of vulnerability of nodes that have not received the information based on the flow of the negative campaign, and a measure of reachability of nodes from the source. Nodes susceptible to adopting and spreading the information from the negative campaign are identified based on the susceptibility score.