Abstract: A human interaction replacement evaluation system analyzes actions taken by a user with an application on a client device that provides features to replace human interaction services with computer-based services. The results of the action provide an indication of the success of a particular action supported by the application (e.g., whether the action has a positive or negative effect on a key performance indicator) or an indication of how likely the user is to be ready to adopt a particular computer-based service. Recommendations are then provided to the user of the application or a manager of the application indicating actions to use, actions that have negative or positive effects on a key performance indicator, and so forth.

Abstract: A method for associating a team with a meeting for prospective meeting includes receiving a meeting invitation comprising first information, wherein the first information comprises data identifying the prospective meeting attendees, receiving second information for a plurality of teams, wherein the second information comprises data identifying members for each one of the plurality of teams, comparing the first information with the second information to determine a match metric for each one of the plurality of teams, and determining a matching team from the plurality of teams for which the match metric is above a match threshold value. The method further includes, in response to determining that the match metric is below the match threshold value computed for each one of the plurality of teams, creating a new team, and associating one of the matching team or the new team with the meeting for prospective meeting attendees.

Abstract: An apparatus in one embodiment comprises at least one processing platform including a plurality of processing devices. The processing platform is configured to receive a request to deploy one or more applications of a plurality of selected applications, wherein the plurality of selected applications are selected based on a determined role of an individual within an enterprise, and to deploy the one or more applications for at least one user device responsive to the request. The processing platform is further configured to monitor execution of the one or more applications in connection with the at least one user device, to receive and analyze data corresponding to the execution of the one or more applications, and to automatically generate one or more recommendations in connection with the deployment of the one or more applications for the at least one user device based on the received and analyzed data.

Abstract: Apparatuses, methods, and computer program products are provided for improved model compliance. An example method includes receiving a product model that is generated from user data associated with a plurality of users and receiving a first regulation offending model that is non-compliant with respect to a first regulatory factor. The method also includes analyzing the product model with the first regulation offending model and generating a first regulation compliance score for the product model with respect to the first regulatory factor. The method further includes determining whether the first regulation compliance score satisfies a first regulatory factor threshold. In an instance in which the first regulation compliance score fails to satisfy the first regulatory factor threshold, the method includes generating a first violation notification or modify the product model.

Abstract: Weather data, asset variable values, and failure data may be received. A correlation factor may be generated by comparing the weather data and the asset variable values. One or more weather variables may be selected based on the correlation factor. A predicted asset variable value may be determined based on the weather data and the selected weather variables. The weather data and the predicted asset variable values may be compared to predict a failure probability for a first asset segment.

Abstract: Managing ridesharing vehicles by receiving passenger data comprising pick-up and drop-off location data of passengers, recording the passenger data in one or more queues corresponding to one or more pick-up locations of the pick-up location data, and sending information associated with a first pick-up location to a first vehicle. In response to the first vehicle arriving at the first pick-up location, extracting data of passengers exiting the first vehicle at the first pick-up location, retrieving passenger data from a first queue corresponding to the first pick-up location according to a capacity of the first vehicle, and updating a passenger ledger of the first vehicle according to the data of the passengers exiting the first vehicle at the first pick-up location and the passenger data retrieved from the first queue.

Abstract: Techniques to generate a digitally optimized schedule for a construction activity to meet a construction objective(s) of a construction project are disclosed. An artificial intelligence system receives a plurality of input data sets that impact the construction project. Each of the plurality of input data sets is processed to achieve the construction objective(s). The artificial intelligence system processes the plurality of input data sets using a respective ensemble of machine learning models. The artificial intelligence system generates machine learning validated intermediate output data sets corresponding to each of the plurality of input data sets. The artificial intelligence system implements a supervisory machine learning model to generate an optimized schedule for the construction activity based on the machine learning validated intermediate output data sets and the construction objective(s).

Abstract: An energy saving support system according to an embodiment is configured to provide a consumer, who has an electric load to which electric energy is supplied from an electric power supply system within a house, with energy consumption-related information through a photo frame or the like. The information providing apparatus is configured to acquire an acceptability level, which stepwise indicates a degree of interest of the consumer in the energy consumption-related information, and to determine the energy consumption-related information to be newly provided to the consumer based on the acceptability level.

Abstract: Weather data, asset variable values, and failure data may be received. A correlation factor may be generated by comparing the weather data and the asset variable values. One or more weather variables may be selected based on the correlation factor. A predicted asset variable value may be determined based on the weather data and the selected weather variables. The weather data and the predicted asset variable values may be compared to predict a failure probability for a first asset segment.

Abstract: Online retailers may operate a network of computing systems in order to provide an electronic marketplace to customers. The network of computing systems may be responsible for maintaining and providing different data to the customers of the online retailer. When a customer transmits a request to the online retailer the request may be divided into a set of tasks that may be executed in parallel by the computing systems. The data generated by executing the various tasks may be cached for various periods of time. Furthermore, log information may be generated based at least in part on execution of the various tasks. The logs may record data on initial access along with an identifier associated with the cached data. For subsequent tasks requiring cached data the log may include only the identifier associated with the cached data.

Abstract: The present invention solves a very complex problem that is a major obstacles for electric utility industry's power lines vegetation encroachment management business. Vegetation contacts to the high voltage overhead power lines cause flash-over and/or blackout which results in hazardous situations and economic losses. Power line vegetation management is a very cost intensive business process which is essential to ensure safe, reliable and affordable electric energy supply by the electric utilities, transmission and generation owners. This routine electric utility vegetation management related work is mandated and overseen by applicable federal, state or local regulatory agencies. The state-of-the-art vegetation management process involves labor and cost intensive foot-patrol, vehicular patrol, air patrol and airborne LiDAR patrol of power lines. These methods are often inefficient, unreliable, risky and costly.

Abstract: Described herein are improved systems and methods for overcoming technical problems associated with the use of Monte Carlo simulation methods, such as problems associated with applications of Monte Carlo simulation methods that are searching for more definite answers. In some embodiments described herein, improved systems and methods overcome the technical problem of the results of Monte Carlo simulations providing approximations and/or non-optimal results (or at least non-enhanced results). Thus, such embodiments can provide more enhanced answers to limiting risks; and in some cases, such embodiments can even provide optimal answers to limiting risks. In some embodiments, machine learning can be used to provide more enhanced answers to limiting risks; and in some cases, such embodiments can use machine learning to provide optimal answers to limiting risks discovered through Monte Carlo simulations.

Abstract: A method, apparatus, and computer program product for digitally presenting statistically-relevant business insights into a set of business metrics for an organization. A computer system identifies a set of organizational characteristics from human resources data of employees of a plurality of organizations, and applies a selected inclusion criteria to the set of organizational characteristics to identify a set of candidate organizations. The computer system identifies a set of benchmark organizations from the set of candidate organizations, and creates a fixed panel of the benchmark organizations. The computer system applies the fixed panel to the human resources data of employees of a plurality of organizations to create an analysis dataset that consists of human resources data of employees of the benchmark organizations. The computer system generates a business insight into the set of business metrics of the organization based on the analysis dataset, and digitally presents the business insight.

Abstract: A ticket exchange server is configured to determine a number of tickets to distribute for an event. The ticket exchange server accesses, for a stadium, training data describing attendance at historical events, historical opponents of a sports team, and a historical win/loss record of the sports team. The ticket exchange server trains a machine-learned model configured to predict an attendance for a future event at the stadium based on an opponent of the sports team at the future event and a current or predicted win/loss record of the sports team. The ticket exchange server selects an event for the sports team against an opponent and determines a predicted attendance using the machine-learned model. The ticket exchange server identifies a number of tickets greater than a capacity of the stadium to make available based on the predicted attendance and distributes the number of tickets to prospective attendees.

Abstract: Methods, apparatus, systems and articles of manufacture methods, systems, apparatus and articles of manufacture to model ecommerce sales are disclosed. A system to model to eCommerce sales includes a trend identifier to compute commerce metric differences corresponding to products, the commerce metric differences based on first commerce metrics scraped at a first time and second commerce metrics scraped at a second time, a splitter to split the commerce metric differences into a first portion of the commerce metric differences corresponding to a first dataset of eCommerce cooperators, and into a second portion of the commerce metric differences corresponding to a second dataset of eCommerce non-cooperators, a machine learning engine to infer sales data by estimating eCommerce non-cooperators sales based on the second portion of the commerce metric differences, and a sales allocator to estimate sales missing from collected sales data based on the estimate eCommerce non-cooperators sales.

Abstract: A computer-implemented method and an apparatus for providing customer notification detects the presence of a customer in one or more interaction channels from among a plurality of interaction channels. The presence of the customer in the one or more interaction channels is stored as presence information. Attention information corresponding to the customer is determined in connection with the presence information. The attention information indicates a current attention of the customer. A notification is provided to the customer on an interaction channel from among the plurality of interaction channels over which the customer is identified to be active or most likely to be active, based on the presence information and the attention information.

Abstract: In response to detecting that a user of a service provider requires assistance, a computer system determines a predicted user intent associated with the user based on monitoring activity associated with the user, and further determines that a first communication channel corresponds to the determined predicted user intent and causes a communication to be initiated with the user utilizing the first communication channel. The computer system determines a user-initiated intent based on analyzing input received from the user, and based on the user-initiated intent, determines if the user-initiated intent corresponds to the predicted user intent. In response to determining that the user-initiated intent does not correspond to the predicted user intent, the computer system determines that a second communication channel corresponds to the user-initiated intent and causes the communication with the user to be switched to the second communication channel.

Abstract: A plant assistance assessment system 100 that assesses a plurality of nuclear power generation plants 110 includes an abnormality sign monitoring system 121 that monitors an abnormality sign in a plant, based on plant data of the nuclear power generation plants; a fault diagnosis system 122 that performs fault diagnosis on each of devices in the plants, based on abnormality sign detection information; a progress prediction system 123 that simulates progress of the plants, based on fault information; an abnormal phenomenon specification system 124 that specifies a potential abnormal phenomenon in the plants, based on progress prediction information; a risk assessment system 125 that assesses a risk of a fault in the devices in the plants in a probabilistic manner; and an abnormal phenomenon assessment system 126 that assesses likelihood of occurrence of an abnormal phenomenon, based on abnormal phenomenon information and fault probability information.

Abstract: A system may provide virtual energy audits of one or more target buildings. The system may retrieve weather data and energy usage data specific to a given target building from a weather server and a utility server, respectively. The system may store predefined building characteristics corresponding to the given target building in local memory. Based on the weather data, energy usage data, and/or predefined building characteristics, the system may generate one or more building markers that characterize the energy usage and efficiency of the given target building. Building efficiency diagnostics and energy conservation prognostics may be generated based on the building markers and may be sent by the system to be displayed via a user interface of a client device. The energy conservation prognostics may include one or more energy conservation measure recommendations and corresponding predicted cost/energy savings.

Abstract: Methods and systems for optimizing item assortments are disclosed. One method includes receiving a request for an optimized assortment. Data relating to items within a selected initial item assortment and item universe is accessed. Constraints are applied to the items in the assortment to arrive at an optimized item assortment. Constraints include goals for optimization, lock in and lock out rules, and item attribute rules. The method may be performed by a system including one or more computing devices communicating via a network with one or more data storage devices.