Abstract: A construction management system includes a geological data acquisition unit configured to acquire geological data of a work target, and a three-dimensional data acquisition unit configured to acquire three-dimensional data of the work target, where the three-dimensional data acquisition unit is configured to acquire, based on the geological data, three-dimensional data including a boundary between geologies of the work target.

Abstract: Systems and methods are disclosed for optimal utilization of machines for performing tasks across a predetermined area. A request may be received to initiate a job on a predetermined area, the job comprising a plurality of tasks associated with a plurality of machines. In response to the request, a first machine of the plurality of machines may be deployed to the predetermined area to execute a first task of the plurality of tasks autonomously. A deployment event may be determined based on characteristics of the first machine and a second machine, and based on characteristics of the predetermined area. The second machine to the predetermined area, upon detection of the deployment event, to execute a second task of the plurality of tasks autonomously.

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: Embodiments as disclosed provide data processing systems and methods for controlling an automated survey system. One embodiment comprises: a processor; a data store storing a plurality of transactions thereon, each transaction comprising transaction metadata and a voice session recording of an inbound call, the transaction metadata for each transaction comprising an identifier for that transaction; a non-transitory computer readable medium having instructions executable on the processor for: generating, by the processor, a worklist for the survey campaign to control conducting of surveys by an automated survey system that is configured to execute the worklist, the worklist comprising a work item for each of the set of transactions and each work item comprising transaction identification data for a transaction from the set of transactions and contact information for the survey target for the transaction corresponding to the transaction identification data in the work item.

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: Various embodiments of the present disclosure provide a casino patron engagement system that facilitates engagement among casino employees and casino patrons to engender patron loyalty.

Abstract: Embodiments forecast demand of an item by receiving historical sales data for the item for a plurality of past time periods including a plurality of features that define one or more feature sets. Embodiments use the feature sets as inputs to one or more different algorithms to generate a plurality of different models. Embodiments train each of the different models. Embodiments use each of the trained models to generate a plurality of past demand forecasts for each of some or all of the past time periods. Embodiments determine a root-mean-square error (“RMSE”) for each of the past demand forecasts and, based on the RMSE, determine a weight for each of the trained models and normalize each weight. Embodiments then generate a final demand forecast for the item for each future time period by combining a weighted value for each trained model.

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: Enterprise organizations may use observational data to gather information about user experiences with their products and tools. For instance, patients with kidney failure may undergo dialysis treatment in order to remove toxins and excess fluids from their blood. The dialysis treatment may be performed at a hospital or clinic, or in a user's home, and the enterprise organization may use gathered information to gain understanding of user experiences with their dialysis machines and services. A user experience computing system gathers and processes user experience information from across the enterprise organization. Using stored observation data (e.g., surveys, studies etc.) in its smallest common form, the computing system may use this data as building blocks for creating more complex data objects (e.g. journey matrices and/or empathy gardens) using inputs from multiple different sources, and to facilitate presenting this information in an effective and empathetic way to product developers.

Abstract: A block storage service analyzes customer behaviors as external signals to the health of the block storage service. In one example, using rules set by a customer for a health monitoring service, the block storage service can gain insights into what the customer cares about. The customer rules can then be used to setup internal monitors within the block storage service. If the internal monitors are triggered, the block storage service can proactively correct problems before the customer alarm thresholds are reached. For example, customer volumes can be moved to increase performance characteristics. In some cases, if the customer has too much performance capability, the customer volume can be moved to a less costly alternative.

Abstract: A method, apparatus and computer program product are provided for providing resource adequacy intelligence information. A user may configure organizational data relating to various levels within an organizational hierarchy. Various assumption data, including quantifiable target developments of an organization, at any level of the hierarchy, may be configured. A monitoring engine monitors actual values of metrics provided by integrating systems, and/or predicted values predicted based on the actual values, relative to target values calculated according to assumption data. Alert conditions relating to metrics, and for any level of the hierarchy may be generated in response to the monitoring and provided via a user interface. Intelligence information relating to workforce needs, location optimization, and real estate needs is also provided.

Abstract: The present disclosure provides a method and system for predicting building energy consumption based on a Holt-Winters and an extreme learning machine, the method including: constructing a building simulation model based on actual operation parameters of a building to obtain an original energy consumption data set of the building; decomposing the original energy consumption data set to obtain a linear energy consumption data set and a nonlinear energy consumption data set; performing prediction on the linear energy consumption data set by using a trained Holt-Winters model to obtain a linear energy consumption prediction result; and inputting the nonlinear energy consumption data set, the original energy consumption data set, and the linear energy consumption prediction result into a trained extreme learning machine model to output a building energy consumption prediction value of the building simulation model.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to identify publisher advertising behavior. An example disclosed method includes initiating a first probing effort of an Internet publisher of interest to establish a baseline advertising ratio for a plurality of advertisers, determining a first advertising deviation based on a difference between the baseline advertising and a local advertising associated with a first geography of interest, and establishing a first probing frequency for the first geography of interest based on the first advertising deviation.

Abstract: Aspects of the present disclosure generally relates to a method including receiving user data and identifying at least a domain target for the at least a domain as a function of the domain-specific data. Also, the method may include generating a plurality of candidate schedules. Further, the method may include selecting an optimal user schedule from the plurality of candidate schedules. Moreover, the method may include presenting, at a remote device, the optimal user schedule to a user, and tracking, by the computing device, a user's progress with regard to the optimal user schedule.

Abstract: A dynamic next-stop or next-item recommendation system that is built entirely from raw card transaction data logs. These data logs contain rich transaction data between cardholders and merchants. A query network approach is constructed for geometrical expressivity and automatically learns the inherent class-hierarchy. To ensure scalability and interpretability of the approach, merchants or entities are grouped into interpretable categories and propose a quadtree-based spatial decomposition of the underlying geography. A two-step recommendation process initiates: (1) predict next-merchant quadtree-box and category combination (2) recommend merchants within the predicted combination. This novel neural architecture may handle the hierarchical classification task in the first part of the recommendation system and compare the methods to previous state-of-the-art approaches in related areas.

Abstract: A system for interactive product sampling and obtaining real-time consumer feedback to generate qualitative insights is described. The system may include an interactive imaging device, a sampling subsystem, a graphical user interface, a back-end system. The sampling subsystem dispenses product samples and obtains audio, video, or textual feedback from consumers. The system may perform sentimental and emotional analysis of video feedback to capture facial expressions and reactions of the consumer consuming the product samples. The system may use a trained model to generate qualitative insights from the feedback. Related methods, computer readable media, computer program product, apparatuses, and techniques are also described.

Abstract: A device may detect a trigger to perform a benchmarking task. The benchmarking task may include a first benchmarking of a first resource utilization associated with one or more tasks completed via an automated procedure. The benchmarking task may include a second benchmarking of a second resource utilization associated with the one or more tasks completed via a manual procedure. The device may determine project data relating to a project platform based on detecting the trigger to perform the benchmarking task. The device may process the project data relating to the project platform to benchmark the project. The device may generate a recommendation relating to completion of the one or more tasks using the automated procedure or the manual procedure. The device may communicate with one or more other devices to perform a response action based on the recommendation.