Abstract: A method may include receiving a request to save the exception to the first rule; in response to the request, updating the user interface, wherein: the first portion is updated to include a parameter of a second rule to exclude a subset of meetings from the ECDS; the second portion is updated to include an impact metric that indicates a percentage of meetings excluded from the ECDS based on an application of the second rule to the ECDS; and the third portion is updated to include selectable elements for creating an exception to the second rule; and a fourth portion of the user interface includes an indication of a number of meetings excluded from the ECDS based on application of the first rule with any exceptions to the first rule.

Abstract: Embodiments for implementing intelligent customer journey prediction and customer segmentation of a processor in a computing environment. A response outcome of a customer journey for a user may be predicted according to an assigned score based on one or more discriminatory sequence patterns identified between one or more groups of customers using one or more machine learning operations.

Abstract: Embodiments of this application provide a seed group spreading method performed at a server. The method includes the following steps: obtaining a positive sample set; obtaining a negative sample set; concatenating each positive sample in the positive sample set with a corresponding positive sample feature to form a positive sample feature vector, and concatenating each negative sample in the negative sample set with a corresponding negative sample feature to form a negative sample feature vector; obtaining a target sample feature set from the positive sample feature vector and the negative sample feature vector according to at least two of a target group index, an information gain, and a logistic regression model; and sending the target sample feature set to a decision end, receiving feedback information of the decision end, and determining, according to the feedback information, whether to spread the seed group.

Abstract: A computer implemented method and system of setting values of parameters of nodes in an omnichannel distribution system, the method comprising is provided. Input parameters are received from a computing device. Historical data related to the network of nodes is received from a data repository. A synthetic scenario is determined based on the received input parameters and the historical data. Each node is clustered into a corresponding category. For each category of nodes, key parameters are identified. A range of each key parameter is determined based on the synthetic scenario. A number of simulations N to perform with data sampled from the synthetic scenario within the determined range of each key parameter is determined. For each of the N simulations, a multi-objective optimization is performed to determine a cost factor of the parameter settings. The parameter settings with a lowest cost factor are selected.

Abstract: A computer implemented method and system of calculating labor resources for a network of nodes in an omnichannel distribution system. Input parameters are received from a computing device of a user. Historical data related to a network of nodes is received, from a data repository. A synthetic scenario is determined based on the received input parameters and the historical data. For each node, key parameters are identified and set based on a multi-objective optimization, wherein the multi-objective optimization includes a synthetic inventory allocation to the node based on the synthetic scenario. A synthetic labor efficiency is determined for the node from the synthetic scenario. Labor resources are calculated based on the synthetic inventory allocation for the synthetic scenario. The labor resources of at least one node are displayed on a user interface of a user device.

Abstract: Methods and systems for managing inventory movements are disclosed. Transfer orders are issued to move inventory from location to location in response to real-time demand events. One method includes receiving an inventory request in response to demand signals. The inventory request is analyzed to determine if inventory needs to be moved within the supply chain to satisfy the request. Origin locations are identified that have available stock of the requested items. Transfer orders are issued for each movement on an individual item basis regardless of the type of event that prompted the transfer. The transfer management system responds in real-time to inventory demands from both online and in-store sales.

Abstract: Embodiments provide a computer-executable method for programmatically generating one or more survey queries. The method includes accessing information on a commercial entity or object. The method also includes, based on the accessed information, determining an attribute descriptor associated with the attribute. The method further includes programmatically generating a survey query indicating the attribute descriptor. The method further includes transmitting one or more computer-executable instructions to a computing device to cause a visual display device to render a user interface, the user interface displaying the survey query and enabling user input in response to the survey query.

Abstract: A plan model system provides interactive graphical user interfaces allowing users to view and navigate to multiple alternative views of measures modeled in one or more planning models. A modeled event is provided by a user relating to a measure of a particular plan model modeling outcomes of a particular business domain of a business organization. An effect of the event on values of one or more measures of the plan model is determined. A graphical representation is presented in the graphical user interface illustrating the effect.

Abstract: Disclosed are blockchain-based systems and methods for analyzing and tracking work performance. An example method may commence with detecting a plurality of actions performed by one or more users with regard to one or more digital files. The method may continue with creating a timestamp for each of the plurality of actions. The method may further include generating a hash value for each of the plurality of actions. The method may continue with storing the hash value and the timestamp associated with each of the plurality of actions to a record on a blockchain. The method may further include analyzing the hash value and the timestamp associated with the plurality of actions of the one or more users to evaluate the work performance of the one or more users.

Abstract: A system for providing a visual display of a visitor's journey pathways through various digital touchpoints and quantitative measurements of the visitor's interaction with each digital touchpoint includes an online visitor meta-data database, an online images database, a visitor journey analytics code, a visitor journey analytics engine, a computing system, and a user interface. The visitor journey analytics code is embedded in each digital touchpoint and the visitor journey analytics code extracts visitor meta-data associated with each digital touchpoint that a visitor visits and uploads them to the online visitor meta-data database. The visitor journey analytics engine includes a customer journey analytics processing software product that receives visitor meta-data and specific online images for each digital touchpoint a visitor visits, calculates a visitor experience performance index for each digital touchpoint, and records visitor's journey pathways through various digital touchpoints.

Abstract: Methods, apparatuses, and computer program products are provided for automatically identifying a shortest duration of time for an aspect of an operation. Electronic data related to instances of past operations of at least one vehicle is received. The data comprises respective available durations of time and actual durations of time for an aspect of the past operations. A candidate data set is generated by removing data related to past operations identified as isolated instances of available durations of time and actual durations of time. A mathematical function is generated that fits the candidate data set. An instance from the candidate data set with the shortest actual duration of time that is less than a threshold distance from the mathematical function is identified. The actual duration of time for the identified instance is assigned as a future duration of time for future operations of the at least one vehicle.

Abstract: Systems and methods relate to predicting improved operating hours for a merchant. For example, a method may include determining operating hours of a target merchant; identifying one or more merchants other than the target merchant having one or more common characteristics with the target merchant; obtaining transactional data indicating customer transactions at the one or more merchants other than the target merchant; computing an estimate of potential customer transactions at the target merchant during a the period of time not within the operating hours by processing input data including the obtained transactional data using a trained machine learning model to produce the estimate, the estimate being a number or value of consumer transactions missed as a result of the target merchant being closed during the period of time; and transmitting, to the target merchant, information indicating the computed estimate.

Abstract: Crowdsourcing using active learning is described, for example, to select pairs of tasks and groups of workers so that information gained about answers to the tasks in the pool is optimized. In various examples a machine learning system learns variables describing characteristics of communities of workers, characteristics of workers, task variables and uncertainty of these variables. In various examples, the machine learning system predicts task variables and uncertainty of the predicted task variables for possible combinations of communities of workers and tasks. In examples the predicted variables and uncertainty are used to calculate expected information gain of the possible combinations and to rank the possible combinations. In examples, the crowdsourcing system uses the expected information gain to allocate tasks to worker communities and observe the results; the results may then be used to update the machine learning system.

Abstract: The present disclosure relates to the field of a system that maps employees' sentiments, and envisages a system for mapping employees' sentiments comprising a database, an input unit, a parser, a filter unit, a lexical analyse), an identifier, a mapping unit, an aggregator, a sentiments analyser, and a computation unit. The employee inputs are received through the input unit. The parser parses the inputs and generates tokens that are filtered based on the filter unit. Keywords are extracted from pre-determined list of keywords based on filtered words which are mapped with pre-determined group of themes and quantitative score based on the weightage score is computed by pre-determined weightage scores. The sentiments analyser analyses employee sentiments, based on quantitative score and computation unit computes a relationship between employee sentiments, employee feedback and employee performance.

Abstract: A method for determining a risk of an emotional response of an audience to at least one publication is described. Additionally, a computing device for determining a risk of an emotional response of an audience to at least one publication is described. Moreover, a computer-readable storage device having processor-executable instructions embodied thereon, for determining a risk of an emotional response of an audience to at least one publication, is described.

Abstract: A method and system for automatically creating and assigning assembly labor activities (ALAs) to a bill of materials (BOM) with a cloud SaaS service. ALA templates are automatically selected and populated for the BOM including labor activities, and other construction related activities, required to build a desired physical structure (e.g., building, etc.) and used to automatically create the ALAs associated with a particular BIM or set of BOM Items. A Critical Path Method (CPM)—Work Time Schedule (WTS) is automatically created. The CPM-WTS along with BOM information is used to automatically create a cost estimate report for building the desired physical structure created.

Abstract: Analyzing a purchase decision made by a user includes tracking locations of a mobile device within a retail store to form a proximity history, the proximity history capturing information relating to items within the retail store in which the user expresses interest, with a point of sale (POS) system, determining purchase information for each of the items in which the user expresses interest in, the purchase information indicating whether an item in which the user expressed interest is or is not purchased, and after the purchase, analyzing the proximity history and the purchase information for each of the items in which the user expressed interest to create a purchase decision analysis, the purchase decision analysis to identify which of the items have a proximity history exceeding a threshold that indicates the user was undecided whether to purchase or not to purchase that item while shopping in the retail store.

Abstract: The present disclosure describes a talent-identification system that can be used by companies to assist in the recruitment process for new employees. Additionally, the system can be used by job seekers to determine ideal career fields and industries. The system employs an array of neuroscience-based tests to assess a user's career propensities, after which the system can provide career recommendations to the user or report on employment suitability of the user to a company.

Abstract: Dynamic task discovery may be implemented for performing workflow tasks. Input may be received from a workflow engine via static interface upon which a task may be performed that is part of a workflow. A version of the task may be dynamically determined according to dynamic task configuration data. The discovered version of the task may be performed and output notification of completion may be sent to the workflow engine. In some embodiments, the dynamic configuration for a task may be modified such that one performance of the task in a workflow may be according to a different version of the task than another performance the same task in the same workflow. In some embodiments, task templates with dynamically discoverable tasks may be generated by a workflow engine service in order to be implemented as tasks in a workflow.

Abstract: A method may permit a consumer to manage behavioral data. The method may include receiving, at an infrastructure device, parameters provided by an administrative device over a local area network (LAN), and configuring, based on the received parameters, the infrastructure device for collection and control of consumer managed behavioral data (CMBD) associated with at least one client device. The method may further include monitoring, at the infrastructure device, data transmitted and received by the at least one client device, and identifying, by the infrastructure device, CMBD from the monitored data based on the received parameters. The method may further include performing actions associated with the at least one client device based on the CMBD and the received parameters.