Abstract: A method for providing a user interface in a low-code or no-code development platform includes generating, by a computing system, a graphic user interface of an application development program. The graphic user interface includes: a first area including a list of blocks; a second area including a structured data object comprising nodes corresponding to one or more of the blocks; and a third area including a parameter field of a selected one of the nodes, wherein the parameter field is configured to receive user input defining both a static string and a dynamic variable.

Abstract: Systems, methods, and computer-readable storage media for recommending computational commands based on a weighted, ranked hierarchical graph. The system converts a map of intended user actions to canonical actions (commands) into a graph representation. Then, via a chatbot algorithm, the system receives an initial intent as a request by a user of the chatbot algorithm. Based on the popularity of alternative canonical actions, the system makes recommendations of alternative actions which are similar to the initial intent provided by the user.

Abstract: A computer-implemented method, computer system, and computer program product for deleting a file from a storage medium. A file that is marked for automatic deletion is identified. A deletion time at which the file is to be deleted from the storage medium is identified. A visual indicator associated with the file is displayed. The visual indicator changes over time to provide an indication as to a nearness of the deletion time.

Abstract: A method and apparatus visualizing compensation adjustments for employees of organization. A computer system identifies a number of merit groups for a group of employees based on employee evaluation for employees in the group of employees. The computer system identifies a number of compensation adjustment parameters. The computer system applies the number of compensation adjustment parameters to a compensation distribution of the group of employees to determine a compensation adjustment for each merit group. The computer system determines impact of the compensation adjustment on the compensation distribution of the group of employees. The computer system displays the impact of the compensation adjustment in a compensation adjustment scenario.

Abstract: A method, computer system, and computer program product are provided for managing time record events. Time record events are collected for a number of users. Each time record event includes a geolocation of one of a number of users. The time record events and geolocations for each of the number of users are models via machine learning. A current geolocation for a given user is identified. A suggested event is predicted based on the current geolocation and a current time. The suggested event is pushed to the user.

Abstract: Asynchronous messaging on an instant messaging system is provided. The method comprises receiving an instant message from a send addressed to a recipient on the instant messaging system and determining a current user status of the recipient. Responsive to a determination the recipient is currently available, the instant messaging system sends the instant message to the recipient in real time. Responsive to a determination the recipient is currently unavailable, the instant messaging system, according to sender preferences, sends the instant message to the recipient via an alternative communication system or stores the instant message in a queue until triggered to send the instant message when the current user status of the recipient changes to available.

Abstract: A method of sparse intent clustering is provided. The method comprises identifying features in a number of electronic user reports created by a user and contained in a database, wherein the features include a title and description. The features of each user report are encoded into a binary vector. The binary vector for each user report is fed into an autoencoder neural network that creates a N-dimensional vector representing the user report. The float vectors representing the user reports are projected into a N-dimensional space. The float vectors are clustered according to cosine similarities, wherein each vector cluster represents an intent of the user in creating the reports. The intent of each vector cluster is then labeled.

Abstract: A method, computer system, and computer program product that aggregates sample data regarding a plurality of factors associated with work scheduling, employee compensation, and employee turnover; performs iterative analysis on the sample data using machine learning to construct a predictive model; populates, using the predictive model, a database with predicted values of employee turnover in relation to work scheduling and employee compensation; converts the predicted values of employee turnover in the database into percentages of observed values of employee turnover for a selected group of employers over a specified time period to create indices of employee turnover; and rank orders the selected employers according to their indices of employee turnover.

Abstract: A method of latent intent clustering is provided. The method comprises encoding identified features in a number of electronic user reports in a database. A binary matrix is created, wherein each row of the binary matric represents a different report and each column represents a different available feature. A 1 is placed in each cell of the matrix that matches a feature present in a user report. Cosine similarities are calculated for the user reports, and a similarity matrix is created, wherein each row and column of the binary matrix represents a different report, and wherein the cosine similarities of the reports are placed in corresponding cells of the matrix. The reports are clustered according to the cosine similarities. Features common to reports in each cluster are identified, and an intent of each report cluster is labeled according to the common features.

Abstract: Analyzing chatbot/employee dialogs is provided. An analysis of a dialog between a chatbot manager and a plurality of employees regarding a current corporate topic is performed using an artificial intelligence component. Relevant information regarding the current corporate topic is extracted from the dialog based on the analysis. Insights corresponding to the relevant information regarding the current corporate topic are generated using the artificial intelligence component. The relevant information regarding the current corporate topic and the insights are displayed in a dashboard on a client device of a human resource agent.

Abstract: A method, apparatus, system, and computer program product for processing an on-demand payroll request. In one illustrative example, an on-demand payroll microservice receives a request for an unscheduled payroll to an employee. The on-demand payroll microservice retrieves payroll information for the employee from a first set of microservices. The on-demand payroll microservice submits the payroll information to a second set of microservices for payroll calculations. In response to the second set of microservices completing the payroll calculations, the on-demand payroll microservice retrieves the payroll calculations through the first set of microservices. The on-demand payroll microservice displays the payroll calculations. In response to receiving approval of the unscheduled payroll, the on-demand payroll microservice submits the payroll calculations to the second set of microservices for payroll processing.

Abstract: A method, computer system, and computer program product are provided for generating reports. Existing reports are collected and modeled to determine a number of contexts. An index of the existing reports is generated according the contexts determined by the modeling. a predicted context of a new report is predicted according to the modeling. According to the index, suggested reports are identified based on the predicted context for the new report. The suggested reports are presented in a graphical user interface.

Abstract: Managing and applying human resources data comprising aggregating employee transaction data for an organization. A number of human resources-related attributes are evaluated across heterogeneous transaction data. The employee transaction data is classified via statistical machine learning into a number of normalized codes according to the human resources-related attributes, a user interface is presented to adjust a number of organizational operating procedures according to the normalized codes.

Abstract: A method for accessing information. A computer system receives a request for a piece of the information stored in a location between client computer systems and sources of the information. The information has formats for the information in the location. The formats for the information are controlled by the sources of the information. Each of the sources is assigned to control a group of portions of the information in the location. The computer system identifies the piece of the information corresponding to the request. The computer system returns a response to the request for the piece of the information, enabling simplifying access to the information in different formats.

Abstract: Systems, methods, and computer-readable storage media for responding to a query using a neural network and natural language processing. If necessary, the system can request disambiguation, then parse the query using a trained machine-learning classifier, resulting in at least one of an identified subject or an identified domain of the text query. The system can determine if the user is authorized to retrieve answers to the query and, if so, retrieve factual data associated with the query. The system can then retrieve a response template, and fill in the template with the retrieved facts. The system can then determine, by executing a machine comprehension model on the filled response template, a probable readability token, portion of text, of at least a portion of the filled response template and, upon identifying that the probable readability is above a threshold, reply to the text query with the at least a portion of the filled response template.

Abstract: A method for proving identity when registering for a service includes presenting by the entity a user with options for registering for the service, wherein the options comprise validating an identity of the user through a trusted partner. The method includes receiving, by the entity, user data from the trusted partner responsive to the user logging into a page on the trusted partner. The method includes validating the user identity for the service responsive to a determination that a user identifier from the trusted partner matches a user identifier on record with the entity. The method includes populating entity user data for the service according to the user data received from the trusted partner responsive to successfully validation of the user identity. In embodiments, a risk analysis score is determined for the user and registration steps for registering are selected based on comparison of the registration score with a threshold.