Abstract: The present application includes a method and system for real-time predictive scheduling. The system receives information from at least one workload input and at least one personnel input, calculating an initial schedule based on the information and on analytics rules in a scheduling analytics engine. The system then allocates incoming workloads to customer service representatives according to the initial schedule, while monitoring adherence to the initial schedule by calculating deviation from schedule adherence. If the deviation from schedule adherence exceeds an acceptable deviation from schedule adherence within the analytics rules, the system calculates an updated schedule.

Abstract: In an illustrative embodiment, an automated system assesses risks associated with real estate entities. The system may include computing systems and devices for extracting data attributes for real estate entities from received source data, and the extracted data attributes may each be associated with a particular data level for a real estate entity. The system can link data attributes in adjacent data levels with unique linkage information and compute metrics for each of the real estate entities from the data attributes where each computed metric may be associated with one of the data levels. The system can assess an amount of risk associated with each of the real estate entities based on the computed metrics and present the assessed amount of risk for one or more real estate entities to a remote computing device of a user responsive to receiving a risk assessment request.

Abstract: An apparatus, method, and computer program product are provided for the improved and automatic prediction and modeling of one or more channels and relevant conditions through which resources may be directed to users in an environment where resource demand, utility, and perceived value vary over time. Some example implementations employ predictive, machine-learning modeling to facilitate the use of multiple disparate and unrelated data sets to extrapolate and otherwise predict the future needs for certain resources and identify the channels and conditions that may be employed to meet such future needs. An apparatus, method, system, and computer program product are provided for improved generating, adjusting, and/or facilitating approval of a resource offer set. Some example implementations employ one or more predictive models.

Abstract: Described herein is a computer implemented method for maintaining a plurality of issues, each issue having an associated rank value, the rank values of the plurality of issues defining an order of the plurality of issues. The method comprises receiving a rank operation request to change the rank of a subject issue; determining relevant issues to the rank operation request; and attempting to acquire locks on each of the relevant issues. In response to successfully acquiring locks on each of the relevant issues a new rank value for the subject issue is calculated and saved.

Abstract: An apparatus, method, and computer program product are provided for the improved and automatic prediction and modeling of one or more channels and relevant conditions through which resources may be directed to users in an environment where resource demand, utility, and perceived value vary over time. Some example implementations employ predictive, machine-learning modeling to facilitate the use of multiple disparate and unrelated data sets to extrapolate and otherwise predict the future needs for certain resources and identify the channels and conditions that may be employed to meet such future needs. An apparatus, method, system, and computer program product are provided for improved generating, adjusting, and/or facilitating approval of a resource offer set. Some example implementations employ one or more predictive models.

Abstract: The innovation disclosed and claimed herein, in one aspect thereof, comprises systems and methods of validating models guided by machine learning algorithms. The innovation can begin by receiving a risk model for validation having multiple sets of data. A first data set is selected from as an input. Outputs are generated for validation. One output can be generating a second set of analysis results using a comparable algorithm to the risk model. Another output can be generating a second set of variables and transformations using a machine learning algorithm and an untransformed set of the selected variables to assess the set of selected transformations. Another output can be generating a third set of variables using one or more machine learning algorithms and an extended feature set of variables to assess the selected variables. The outputs are compared to the analysis results, coefficients, selected variables, and selected transformations. A report of the comparison is generated.

Abstract: Disclosed herein are system, method, and computer program product embodiments for recommending a service provider. An embodiment operates by receiving a search request specifying a service request by a user and location for the requested service, retrieving prior financial transactions of the user to purchase the service from a database, and determining a preference of the user based on the retrieved prior financial transactions. The embodiment further operates by applying the preference to a model trained to output a recommended service provider and selecting the recommended service provider for display on a user's device. The model more likely recommends service providers in the location having a higher ratio of tip-to-price relative to other providers for the service in the location based on a history of prior financial transactions of a plurality of users.

Abstract: A system and method are disclosed including a planner having a processor and memory. The planner models a supply chain network over a planning horizon having one or more time buckets and a production line to produce one or more products using one or more campaign operations and one or more campaignable resources. The planner further formulates a supply chain master planning problem comprising a hierarchy of objective functions and one or more constraints and segments a campaign planning problem into three stages. The planner solves a first stage to determine prioritized production demands on campaignable buffers, solves a second stage to determine a timing and a sequence for allocating campaignable resources to campaignable buffers, and solves a third stage to determine a quantity of products to produce on campaignable resources.

Abstract: A neurological profile associated with introversion/extroversion levels, simultaneous visual element processing capability, and/or dynamism processing capability, etc., is determined to select market categories and stimulus material targeted to the particular neurological profile. The neurological profile is determined using information such as user input, user activity, social and environmental factors, genetic and developmental factors, and/or neuro-response data. The neurological profile can be matched with corresponding neurological profile templates to select market categories and stimulus material.

Abstract: The present application includes a method and system for real-time scheduling reallocation. The system receives a schedule which allocates customer service representatives (CSRs) to channels and queues based on analytics rules as well as the forecast work patterns and information on CSR skills and shift patterns. The system then monitors adherence to the schedule by comparing the difference between forecast and current volume and type of work to a reallocation threshold at predetermined intervals. If the difference extends beyond the reallocation threshold, the system reallocates CSRs to update the schedule.

Abstract: The present application includes a method and system for real-time predictive scheduling. The system receives information from at least one workload input and at least one personnel input, calculating an initial schedule based on the information and on analytics rules in a scheduling analytics engine. The system then allocates incoming workloads to customer service representatives according to the initial schedule, while monitoring adherence to the initial schedule by calculating deviation from schedule adherence. If the deviation from schedule adherence exceeds an acceptable deviation from schedule adherence within the analytics rules, the system calculates an updated schedule.

Abstract: Disclosed is a task map providing apparatus for displaying one or more tasks, the apparatus including a memory and a processor electrically connected with the memory. The processor may be configured to generate the one or more tasks by receiving, from a task instructor who instructs recording a note through the one or more tasks, information on a task performer instructed to record the note corresponding to the one or more asks, generate progressive bars to correspond the one or more tasks, the progressive bar representing how many days have passed and remain with respect to a note recording due date by which the task performer needs to record the note.

Abstract: Techniques are described for machine learning-based generation of target segments is leveraged in a digital medium environment. A segment targeting system generates training data to train a machine learning model to predict strength of correlation between a set of users and a defined demographic. Further, a machine learning model is trained with visit statistics for the users to predict the likelihood that the users will visit a particular digital content platform. Those users with the highest predicted correlation with the defined demographic and the highest likelihood to visit the digital content platform can be selected and placed within a target segment, and digital content targeted to the defined demographic can be delivered to users in the target segment.

Abstract: An exemplary embodiment of the present application is a system and method for work allocation optimization. In the present disclosure, analytics are applied to work items while the work items are waiting in a work queue in order to optimize the routing and allocation of work items to agents in the most efficient manner possible, while optimizing the utilization of agents. By performing a look ahead at more than the initial work item, the system assesses the agent skills required by imminent work items in the work queue. This is then compared to a skillset of each available and/or soon to be available agent in order to achieve the optimal allocation of the work items to maximize utilization of agents. The work items are then routed to the agents accordingly.

Abstract: In the present disclosure, analytics are applied to work items while the work items are waiting in a work queue in order to optimize the routing and allocation of work items to agents in the most efficient manner possible, while optimizing agents being assigned to work items they are most qualified to handle. By performing a look ahead at more than the initial work item, the system assesses the agent skills required by imminent work items in the work queue. This is then compared to a skillset of each available and/or soon to be available agent in order to achieve the optimal allocation of the work items to maximize the work item being assigned the best qualified agent. The work items are then routed to the agents accordingly.

Abstract: The innovation disclosed and claimed herein, in one aspect thereof, comprises systems and methods of validating models guided by machine learning algorithms. The innovation can begin by receiving a risk model for validation having multiple sets of data. A first data set is selected from as an input. Outputs are generated for validation. One output can be generating a second set of analysis results using a comparable algorithm to the risk model. Another output can be generating a second set of variables and transformations using a machine learning algorithm and an un-transformed set of the selected variables to assess the set of selected transformations. Another output can be generating a third set of variables using one or more machine learning algorithms and an extended feature set of variables to assess the selected variables. The outputs are compared to the analysis results, coefficients, selected variables, and selected transformations. A report of the comparison is generated.

Abstract: A system of producing files containing information about printed mailpieces comprising a plurality of folder inserters (22, 24, 26) each having a reading device for extracting at least a job ID and a mailpiece ID, the system comprising at least: a processing node (32, 34, 36) adapted to check the job ID and mailpiece ID from the printed mailpiece and to check out a relevant job against locally held rules; a storage node (38) connected to the processing node and adapted to store the job ID and mailpiece ID sent by the processing node; and an interface node (40) connected to the storage node and adapted to import and export the files.

Abstract: An example embodiment may involve a software application executable on a computing device of a computational instance of a remote network management platform associated with a managed network. The managed network may contain an enterprise resource planning (ERP) system comprised of computing devices of the managed network on which ERP software is executable. The managed network may be granted a number of authorizations to access the ERP system and capabilities thereof. The ERP system may store user-related data for individual users of the managed network who access the ERP system. The software application may communicate with one or more of the ERP clients to access the user-related data, use a set of compliance criteria to identify, within the user-related data, a set of users, and store in memory an indication identifying the set of users as a potential source of non-compliance with the number of authorizations.

Abstract: A construction site status monitoring device is provided including processing circuitry configured to receive sensor data associated with a construction site from a scout device and generate a site map based on the sensor data for deployment of the construction device.

Abstract: An activity recording device includes: a work specifying unit for specifying a work of a worker; a position specifying unit for specifying a position of the worker from a position coordinate of the worker; a state specifying unit for specifying a state of the work of the worker from the position specified by the position specifying unit; and a recording unit for recording, as activity data, the work, the position, and the state in association with an activity time, wherein the position specifying unit includes a position estimation unit and a position correction unit.