Abstract: A method and system are provided in which predictions are generated, using one or more machine learning-based prediction models, for one or more process parameters associated with a running process. Explanation-oriented data elements are generated that correspond to the generated predictions and include confidence indicators associated with the generated predictions. The explanation-oriented data elements are presented in one or more dashboards of a visualization platform. The explanation-oriented data elements are representative of an explanation framework for explaining the predicted business process parameters generated by a machine learning-based prediction model and in a manner so that a user can understand and trust the basis for the predictions to facilitate effective and appropriate intervention in a running process.

Abstract: In an example embodiment, machine learning is utilized to automatically identify pain points of an entity. More particularly, a random forest search algorithm receives inputs from a number of different outside-in data engines. These inputs are segregated in terms of key performance indexes (KPIs), which is then fed to a random forest decision tree. The random forest search algorithm calculates a p-value for each KPI. This p-value may then be used to identify the most relevant KPIs (such as by ranking the KPIs by their respective p-values). Rules are utilized not to identify the pain points themselves, but instead to define sorting preferences (refine the ranking). Based on a combination of the p-values and the evaluation of the rules, the top-N pain points may be identified.

Abstract: Methods and systems to generate a work schedule for a multi-task project include storing, in a memory, a task code and a labor requirement for each task of the multi-task project. The methods and systems also include building, by a processor, a task schedule for the multi-task project. The task schedule includes labor hours, a projected time frame, and worker roles for each task. The methods and systems further include retrieving, by the processor, availability data for workers qualified for the worker roles of each task. The availability data for each worker includes an availability status and a geographic location. The methods and systems also include building, by the processor, the work schedule by assigning workers to job orders based on the task schedule, the worker availabilities, the geographic locations, and the project location.

Abstract: A method, system and computer program product for identifying a geographic market share. Mobility data is acquired from applications running on mobile devices of users located within a geographic area. Mobility data is then used to infer shopping habits within the geographic area. Geo-demographic profiles are then created. The geographic market share is then determined using the created geo-demographic profiles.

Abstract: Example methods disclosed herein include accessing common homes data for a group of common homes, the common homes data including return path data and panel meter data. Disclosed example methods also include accessing common homes data for a group of common homes, the common homes data including first return path data and corresponding panel meter data associated with respective ones of the common homes, grouping the common homes data into view segments, classifying the view segments based on whether the return path data in respective ones of the view segments has matching panel meter data to determine labeled view segments, generating features from the labeled view segments, training a machine learning algorithm based on the features, and applying second return path data to the trained machine learning algorithm to determine whether a media device associated with the second return path data is on or off.

Abstract: Systems and methods for candidate recommendation are provided. Candidate vectors are generated from candidate documents, and an initial ranking is performed according to a distance metric between the candidate vector and an objective vector generated based on an objective document to select a subset of the candidate documents. A feature vector is generated for each of the selected candidate documents. The feature vector includes features derived from a first vectorized representation of content from one of the candidate document and the objective document and a second vectorized representation of content from the one of the candidate document and the objective document. The feature vector is provided to a machine learning model to generate a score for each of the selected candidate documents. The selected candidate documents are ranked according the scores generated at the machine learning model to provide a ranked candidate list.

Abstract: A method for audience recommendation using node similarity in combined contextual graph embeddings can include receiving a merchant identifier of a merchant and generating one or more merchant tags describing merchant data corresponding to the merchant. A set of audience embeddings can be generated from a set of audience auxiliary data using an audience taxonomy and a set of merchant embeddings can be generated from the merchant data relating to the merchant using the one or more merchant tags. The set of audience embeddings and the set of merchant embeddings are used to produce a heterogenous information network of combined audience data and merchant data, which is then analyzed to identify relationships between each audience and the merchant. A score for one or more audiences can be determined based on the relationships between the one or more audiences and the merchant.

Abstract: Systems and techniques may be used for providing information related to an underperforming product. An example technique may include determining, for products in a particular zone of a website, an underperforming product based on pageviews or interaction metrics of users visiting the website. The technique may include identifying a product type of the underperforming product, and outputting a recommendation for display. The recommendation may include at least one replacement product of the product type, other than the underperforming product, to replace the underperforming product in the particular zone.

Abstract: A method may include receiving data from the plurality of databases for an applicant to be placed on one or more waiting lists with one or more requirements. A user profile associated with the waiting list may be created based on the received data, and may be received from the applicant. An applicant ranking on the one or more waiting lists may be determined based on a match between the user profile and the one or more requirements. At least one of a need or a desire of the applicant may be monitored based on periodic activity of the applicant on the one or more waiting lists. Periodic changes to the one or more requirements may be monitored. The applicant ranking may be updated on the one or more waiting lists, and the updated one or more waiting lists may be synchronized with the plurality of databases.

Abstract: The supply chain management apparatus includes: an input unit that receives input information indicating a change in market conditions; a storage unit that stores supply chain information in which constituent companies of a supply chain, T&Cs information in which T&Cs of each of the constituent companies of the supply chain is registered, and a condition for a key performance indicator which should be satisfied, the condition for a key performance indicator being set for each of the constituent companies; a T&Cs calculation unit that, when the input information is received, calculates a supply chain plan corresponding to the change in the market conditions indicated by the input information based on a predetermined calculation method, and when a key performance indicator calculated based on the supply chain plan does not meet the condition for the key performance indicator, changes the T&Cs so that the key performance indicator is optimal.

Abstract: Strategic planning and strategy execution is important in organizations of various sizes and types, such as business and industry, government, and nonprofit organizations. While strategic planning and strategy execution are important, present systems and methods present challenges in providing for a system that links all aspects of strategic planning and strategy execution and communicates strategic planning and strategy execution throughout an organization. The present disclosure provides a system and method with an ability to articulate and align objectives, measures, targets, resources, activities, and outputs with desired outcome(s) and desired impact.

Abstract: An information processing apparatus includes an acquisition unit that acquires work information associated with a content of work and a point in time at which the work was performed, and emotion information that records an emotion of a person who performed the work for each point in time, and a generation unit that generates aptitude information indicating an aptitude for the work for each person by associating the work information and the emotion information using a point in time.

Abstract: Implementations are described herein for using machine learning to determine whether candidate crop fields are suitable for management by particular agricultural entities. In various implementations, a machine learning model may be applied to input data to generate output data. The input data may include a first plurality of data points corresponding to field-level agricultural management practices of an agricultural entity. The output data may be indicative of one or more predicted outcomes of the agricultural entity implementing the field-level agricultural management practices on one or more candidate crop fields not currently managed by the agricultural entity. Based on one or more of the predicted outcomes, one or more computing devices may be caused to provide a user associated with the agricultural entity with information about one or more of the candidate crop fields, and/or one or more parameter inputs of a graphical user interface may be prepopulated.

Abstract: This disclosure describes techniques for analyzing operational data and applying one or more rule sets to identify issues and/or to determine whether action should be taken to prevent or mitigate a future risk event. In one example, this disclosure describes a method that includes receiving, by a computing system, risk data; generating, by the computing system and based on the risk data and a set of rules, an issue relating to an entity; outputting, by the computing system, a request; responsive to outputting the request, receiving, by the computing system, a response to the issue from the entity; storing, by the computing system, information about the response; receiving, by the computing system, information about a risk outcome associated with the issue; and modifying, by the computing system and based on at least one of the response and the information about the risk outcome, the set of rules.

Abstract: An arrangement planning device includes: a collection unit that collects state information indicative of a present-time state of each of storage batteries; a prediction calculation unit that calculates a performance indicator of a degree of wear of each of the storage batteries from the state information; an amount-of-operation acquisition unit that obtains a required amount of operation of the storage batteries at each of places of use, the storage batteries being to be placed in the places of use; a policy acquisition unit that obtains an operation policy for each of the storage batteries; and a placement location determination unit that determines a placement location for each of the storage batteries from the places of use, wherein the placement location determination unit determines the placement location for each of the storage batteries based on the required amount of operation, the performance indicator, and the operation policy.

Abstract: A category recommender system includes a computing device configured to obtain customer information characterizing a customer's interactions on an ecommerce marketplace. The computing device is further configured to determine discovery category rankings for each category of items available on the ecommerce marketplace for the customer based on the customer information, determine repeat category rankings for each category of items available on the ecommerce marketplace for the customer based on the customer information, and determine item rankings for each item in the ecommerce marketplace based on the customer information. The computing device is further configured to merge the discovery category rankings, the repeat category rankings and the item recommendation rankings into final recommendations based on one or more predetermined merging criteria and provide the final recommendations to the customer.

Abstract: Value-added services that allow for a seamless integration of actions related to activities and/or events are provided. A determination is made that an event has started based on scheduled event data or historical information associated with a user. Profile data associated with the user is identified based on the start of the first event. The identity of the user is verified based on a mapping between the profile data and data related to the first event. Further, an activity related to a second event is triggered after completion of a transaction of the first event is completed. A suggested action may be activated based on the trigger event. The suggested action is based on historical information associated with the user and is not a component of the first event or the second event.

Abstract: Disclosed herein are system, method, and computer program product embodiments for enhancing the experience for new sellers when creating listings are described. An embodiment operates by: enabling a new seller to create one or more new listings for an electronic marketplace (EM); determining that a number of the new listings satisfy a predetermined threshold; and enabling the new seller to acquire one or more for sale objects (FSOs) from associated eligible listing(s) on the EM at no or reduced cost. In an embodiment, the new seller is a user who has not previously sold a FSO on the EM, and the eligible listings are (1) listings having an offer price less than or equal to a predetermined maximum mice; and (2) listings by users who have not previously sold a FSO on the EM.

Abstract: According to one aspect, a method includes identifying a machine arranged to be monitored using teleoperations, and obtaining a first request from a first teleoperations arrangement to monitor the machine. The first teleoperations arrangement includes a first teleoperations equipment. The method also includes determining whether to accept the first request from the first teleoperations arrangement, wherein determining whether to accept the first request from the first teleoperations arrangement includes verifying that a first operator of the first teleoperations equipment is certified by the platform and verifying that the teleoperations equipment meets a standard. The first request is accepted when it is determined that the request is to be accepted, wherein accepting the first request includes assigning the first teleoperations arrangement to monitor the machine during a first shift. Finally, the method includes monitoring the first teleoperations arrangement and the machine during the first shift.

Abstract: A system and method for providing personalized presentation of job skills in one or more organizations. The system includes an interface device and a processing device to retrieve, based on one or more identifiers, a set of talent profiles stored in a human resource (HR) information system, calculate, based on the one or more skills in each of the set of talent profiles, an inventory of skills, for each skill in the inventor of skills, calculate a trend value based on timestamps and one or more skills associated with the set of talent profiles, responsive to identifying a first job profile, generate a first skill cloud, the first skill cloud comprising symbols representing skills contained in the inventory of skills arranged in an order determined based on the trend value associated with each skill in the inventory of skills, and present, in a graphical user interface implemented on the interface device, the first skill cloud.