Abstract: An e-commerce based transaction system on a network connected via the Internet to multiple remote computers and mobile phones providing the distribution of hotel room lodging reservations or other lodging sites for location and date of specific events. A central database is hosted on a server and transmitted to individual remote servers or users that can have a respective database of listings from individual brokers oration or other system participants. In the alternative, the blockchain can be a mode of information dissemination. E-commerce transactions are conducted by the system, which performs a number of transaction-related functions, such as posting available hotel room reservations or lodging site reservations for sale, and purchasing spaces for use, resale, brokerage or pure speculation online.

Abstract: A method of automating a workflow may include obtaining a completeness graph including conditions applied to attributes of an entity, determining that a missing attribute subset of the attributes lacks a corresponding value, determining that a condition corresponding to a missing attribute of the missing attribute subset is satisfied, and obtaining a value for the missing attribute. The value may be a result of performing a task in the workflow. The method may further include modifying a state of the entity by assigning the value to the missing attribute to obtain a modified state of the entity.

Abstract: A method may include determining various tasks associated with a user assessment. The method may further include generating a virtual reality (VR) space for the user assessment based on the tasks. The method may further include transmitting, during the user assessment, VR image data to a headset coupled to the user device. The VR image data may correspond to the VR space. The method may further include generating a user assessment recording in response to a user performing tasks in the VR space. The user assessment recording may be based on the VR image data and an avatar of the user based on image data from a camera device coupled to the user device. The user assessment recording may be a mixed-reality recording of the user assessment.

Abstract: Methods, apparatus, and articles of manufacture are disclosed. An example apparatus includes a co-viewing calculator to calculate a co-viewing factor corresponding to a demographic of panelists based on exposure information, an exposure time calculator to calculate a number of census co-viewer exposure minutes based on the co-viewing factor, a data aggregator to determine an aggregate exposure time total based on census exposure information and the number of census co-viewer exposure minutes, and a report generator to generate a report including the aggregate exposure time total.

Abstract: A method of training a neural network to approximate a forecasting error of a passenger-demand forecasting model that includes calculating, using the forecasting model, a historical passenger demand forecast for each key level in a set of key levels and for each departure date in a set of historical departures dates; applying a dropout model to the historical passenger demand forecasts to create a training sample; training, using the historical passenger demand forecasts and the training sample, the neural network, to approximate forecasting errors associated with the forecasting model; calculating, using the forecasting model, a future passenger demand forecast for each key level in the set of key levels and for each departure date in a set of future dates; and approximating, using the trained neural network, the forecasting error associated with the future passenger demand forecasts for the second set of departure dates.

Abstract: Systems and methods for predictive analytics may make innovation success easy to manage by predicting the best process and teams to help teams discover if their ideas can reach ideal outcomes. Leadership may make a portfolio of investments in opportunity areas. Each opportunity area's funds may be broken down into different bets. Each bet fund may have success criteria to determine if an opportunity can continue to the next stage of funding. Each success metric may have blocks that help take ideas to success. Systems and methods may recommend the best block path to success for each idea. Blocks may be recommended based on context including, but not limited to, progress, goals, priorities, team dynamics, and skills. These systems and methods also may empower people to drive success, while engaging interests, saving hours, and eliminating wrong work. Good decisions may be made to maximize ROI, thereby creating innovation success.

Abstract: A method and system for appointment scheduling, the computer implemented method acting a digital rolodex for clients to schedule appointments for any number of services from businesses whereby they may also be provided with live updates of the location of the businesses and their employees when providing services and may receive an invoice for the services as well as pay for the services. The business may have advertisements for the business appear more or less frequent depending on the volume of appointments scheduled in the calendar and may be provided with live updates of the location of the client.

Abstract: The present invention provides self-driven Artificial Intelligence based system and method for operating one or more applications including enterprise application and supply chain management applications. The system includes centralized data lake for storing data received from plurality of distinct sources, a control tower configured for sensing change in attribute of the received data and determining impact of the change on plurality of functions of EA and SCM applications.

Abstract: The present disclosure relates to management of inventories and supply chains and, more particularly, to a predictive inventory management system and methods of use. The method of inventory management, includes: obtaining information associated with an item; predicting demand of the item based on the obtained information; determining whether additional inventory is required based on the predicted demand of the item; and obtaining additional inventory of the item when the current inventory level does not match the predicted demand.

Abstract: A system and method for efficiently determining the fair-share bands of a supply chain planning problem modeled as a multi-objective hierarchical linear programming problem include a processor and memory and are configured to model a supply chain planning problem as a multi-objective hierarchal linear programming problem, assign weights at each band of a fixed number of at least two bands, determine a direction of improved band values from a value of a Key Process Indicator (KPI) calculated from an expected demand and short quantities, wherein the expected demand and short quantities are calculated from the multi-objective hierarchical linear programming problem using a sample generated by Gibbs sampling of a conditional Gaussian Bayesian Network, and generate a supply chain plan.

Abstract: A crop management system including at least one crop monitoring subsystem including at least one crop sensor assembly for sensing at least one crop growth parameter in a predetermined region, at least one field monitoring subsystem including at least one field sensor assembly for sensing at least one field parameter in the predetermined region, an analysis engine receiving an output from at least one of the at least one crop monitoring subsystem and the at least one field monitoring subsystem and being operative to identify at least one anomaly in at least one of the parameters and an anomaly locator operative to provide an output indication of spatial coordinates of at least one location of the at least one anomaly.

Abstract: A text analytics system may predict whether a policy will be adopted. The system may include at least one processor configured to access information scraped from the Internet to identify text data associated with comments expressed by a plurality of individuals about a proposed policy. The at least one processor may be further configured to analyze the text data in order to determine a sentiment of each comment; apply an influence filter to each comment to determine an influence metric associated with each comment; weight each comment using the influence metric; determine based on an aggregate of the weighted comments, an indicator associated with adoption of the policy; and transmit the indicator to a system user.

Abstract: In order to analyze the purchasing situation from the various kinds of information regarding the products sold on the mall style shopping site, a purchasing analysis system for analyzing purchase status of a target product sold on a mall style shopping site has a trading history acquisition unit acquiring information related to a trading history of the target product on the mall style shopping site. The system also has an advertising information acquisition unit acquiring advertising indicators of the target product. Further, the system has an output unit displaying the information related to the trading history and the advertising indicators on a same time axis.

Abstract: The disclosure provides an Internet of Things system and a method for managing a people flow of a public place in a smart city. The method may comprise obtaining pedestrian distribution information in a preset area during a current time period via network from a storage device; determining, by processing the pedestrian distribution information through an area location prediction model, at least one area location in the preset area for a future time period, a population flow load of the area location being greater than a first threshold, wherein the area location prediction model includes a graph neural network model, a graph input into the graph neural network model includes at least two nodes and at least one edge; generating, based on the area location, prompt information; and feedbacking the prompt information to a user terminal of a user platform through a service platform via the network.

Abstract: System and methods for providing a target price for a target vehicle with a target mileage are provided. One exemplary method includes receiving attributes for the target vehicle, receiving prices for sold vehicles having attributes corresponding to the target vehicle attributes, and receiving mileages for the sold vehicles. The exemplary method may further include generating a linear regression model relating the sold vehicle mileages to the sold vehicle prices, and providing the target price for the target vehicle based on the model.

Abstract: A system for optimizing resource allocation includes and/or interfaces with: a set of contextual data sources; a decision-making subsystem; and a set of schedules. Additionally or alternatively, the system can optionally include and/or interface with a set of user interfaces, memory, a set of data collection, and/or any other suitable components. A method for resource optimization includes: receiving a set of inputs; and processing the set of inputs and/or contextual data with a set of models to produce a set of schedules. Additionally or alternatively, the method can include any or all of: training the set of models; pre-processing the set of inputs to supplement the set of contextual data; dynamically adjusting the set of schedules; triggering a set of actions based on the set of schedules; updating the set of models; and/or any other processes.

Abstract: Resource-constrained, multi-period scheduling model for asset investment planning. In an embodiment, asset-related tasks for physical equipment are received, along with a time window. Each of the asset-related tasks is associated with parameter values for each time period within the time window. A resource-constrained project scheduling model is executed to identify an optimal portfolio of the asset-related tasks that satisfies a set of constraints, according to an objective, based on the parameter values for the asset-related tasks. In the optimal portfolio, each asset-related task is assigned to a time span comprising one or more time periods in the time window. The optimal portfolio may then be used to schedule the asset-related tasks in the optimal portfolio, in order to facilitate repair, maintenance, and capital tasks, for example, by automatically dispatching work orders or resources, automatically configuring a state of the physical equipment, informing an asset management system, and/or the like.

Abstract: An online concierge system allows users to order items within discrete time intervals later than a time when an order was received or for short-term fulfillment when the order was received. To account for a number of shoppers available to fulfill orders during different discrete time intervals and numbers of orders for fulfillment during different discrete time intervals, the online concierge system specifies a target rate for orders fulfilled later than a specified discrete time interval and a threshold from the target rate. A trained machine learning model periodically predicts a percentage of orders being fulfilled late, with an order associated with a predicted percentage when the order was received. The online concierge system increases a price of orders associated with predicted percentages greater than the threshold from the target rate. The increased price of an order is determined from a price elasticity curve and the predicted percentage.

Abstract: Coaching systems and methods, and non-transitory computer readable media, include analyzing an agent's interactions to identify knowledge gaps and specific topics where an agent has difficulties. An algorithm uses bootstrap sampling to verify that an agent's scores are significantly different from other agents' scores. The algorithm further uses a mutual information score to find topics that are associated with interactions having a high knowledge gap score.

Abstract: An online concierge system suggests subsequent search queries based on previous search queries and whether the previous search queries resulted in conversions. The online concierge system trains a machine learning model using previous delivery orders and whether initial and subsequent search queries in the previous delivery orders resulted in conversions. When the online concierge system receives a search query to identify one or more items from a customer, the online concierge system parses the search query into combinations of terms and identifies items related to the search query. In response to the search query resulting in a conversion, the online concierge system retrieves a conversion graph and presents a suggested subsequent search query based on the conversion graph. In response to the search query not resulting in a conversion, the online concierge system retrieves a non-conversion graph and presents a suggested subsequent search query based on the non-conversion graph.