Abstract: Task assignments are identified. A dataset that includes one or more electronic messages is received. Then, one or more pending tasks in the dataset are identified, and each of a plurality of people who are mentioned in the dataset is also identified. Then, for each of the pending tasks, one or more of the identified people are identified as potentially being people who are assigned to complete the pending task, and the pending task is associated with these identified one or more of the identified people. For each of the pending tasks, one or more of the identified people are also identified as potentially being people for whom the pending task is to be completed, and the pending task is also associated with these identified one or more of the identified people.

Abstract: A site management system has a site management device located on a fielded site, which has a controller unit integral with a power provision unit, and the power provision unit receives an input voltage via a conductor cable and delivers power to one or more receptacles. Additionally, the system has a plurality of remote devices communicatively coupled to the site management device over a wireless network and at least one off-site computing device communicatively coupled to the site management device. Further, the system has a processor on the controller unit that communicatively couples with at least one remote device, receives data indicative of a unique identifier from the wireless remote device, and determines whether the unique identifier correlates with a remote device of an individual who is permissively on the fielded site.

Abstract: Merchant transaction data for a group of merchants, category transaction data for the group of merchants, and merchant location data for the group of merchants may be obtained for a first time period and a second time period. The merchant transaction data may include a first set of parameters. The category transaction data may include a second set of parameters, and the location data may include a third set of parameters. Additional data during the first time period and the second time period may also be obtained. The additional data may include a fourth set of parameters. The merchant transaction data, the category transaction data, the merchant location data, and the additional data may be analyzed using a machine learning program to generate a set of key parameters to predict merchant performance. A first list of merchants that are predicted to grow may be generated using the key parameters.

Abstract: Embodiments of the present disclosure disclose methods and systems for generating operational alarms for a plurality of clients, the operational alarms being generated by a business performance system, each client being associated with a plurality of Key Performance Indicators (KPIs). An aggregate rank for each client based on ranks of each KPI is generated. For each client: the aggregate rank of the client over one or more time periods is monitored. If the aggregate rank deteriorates over the one or more time periods, a severity indicator is determined based on change of value of each KPI and change of rank of each KPI for the client over the one or more time periods. An operational alarm based on value of the severity indicator is determined. The operational alarm is displayed on a user interface, wherein the operational alarm displays one or more KPIs with highest severity values.

Abstract: Method and system are provided for customer table service management. The method includes receiving sensor load data over time from a customer table. The method analyzes the sensor load data during a waiting time between a time of one or more customers arriving at the table and a time of consumables being served to the table to learn background noise data of the one or more customers. The method further analyzes the sensor load data during a dining time after the time of consumables being served to the table to detect one or more events that require a service action, wherein analyzing the sensor load data during the dining time removes the learnt background noise data to distinguish sensor load data changes relating to consumption of the consumables on the table. The method outputs event detection notifications to prompt the required service action.

Abstract: Systems for using cognitive automation techniques to generate resource recommendations are provided. In some examples, current resource data may be received. The current resource data may include current staffing data, skills associated with current staff, and the like. In some examples, environmental condition data may also be received. The environmental condition data may include current weather information, predicted weather information, power outage information, and the like. The resource data and environmental data may be analyzed using cognitive automation techniques to identify and/or generate one or more resource recommendations. The resource recommendations may include adjustments to staffing, modification of locations at which processes are performed, and the like. The identified or generated recommendations may be transmitted to one or more computing devices.

Abstract: Systems, methods, and other embodiments associated with generating a price schedule are described. In one embodiment, for each customer segment of a plurality of customer segments, a per-segment value of an approximate objective function for the customer segment is determined by an optimizer, and a ratio of the per-segment value to a sum of all per-segment values for the customer segments is computed. The inventory quantity is allocated amongst the customer segments according to the ratio for each customer segment to form an inventory quantity for each customer segment. For each customer segment, a promotion portion of the price schedule that maximizes the objective function by the optimizer is determined. A quantity of remaining inventory allocated to the plurality of customer segments at an end of the regular season is aggregated. A markdown portion of the price schedule for the item that maximizes the objective function is determined by the optimizer.

Abstract: An order entry and order management network is disclosed. Event log data associated with a completed real order and relevant to a scenario is accessed by a computing device. A template is built for the scenario using the event log data. The template is modified as needed based upon predetermined specifications of the scenario. A simulated order is generated by applying the event log data to the template. A simulated workflow is initiated based upon the simulated order. The simulated workflow is a virtualized workflow monitored by the computing device to test the scenario. The computing device monitors network traffic associated with orders. The computing device communicates aspects of the event log data to systems of the order entry and order management network when the computing device identifies network traffic associated with the simulated order in order to process the simulated workflow and test the scenario.

Abstract: A determination is produced as to the number of leads that can be provided from a system to a target business entity, wherein the leads are generated from a plurality of platforms. The platforms may include platforms that comprise system sources for leads, i.e., sources that are internal or organic to the system, for which it is unnecessary to pay third parties for the leads. The platforms may also include platforms that comprise external sources for leads, such that the leads must be purchased from the external sources. In response to parameters related to the target business entity, an estimated number of leads per unit time is generated for a range of payments to the system by the target business entity. The number of leads to be originated from each of the respective platforms is determined by business rules preferences, which may be specified by the target business entity.

Abstract: In one embodiment, a method is provided. The method includes receiving forecast information from sales people in a computer. The method further includes receiving comments on specific entries of the forecast information from non-sales people in the computer. The method also includes receiving changes of the forecast information from the non-sales people in the computer. The method additionally includes providing a display of the comments and the changes to the sales people in an interface to the computer.

Abstract: Systems and methods for providing analytics data to payment facilitators and sub-merchants via a dynamic dashboard.

Abstract: A system for anomaly monitoring in a pre-defined environment includes one or more image capturing devices configured to capture one or more images of the pre-defined environment in real-time, a process detecting component configured to detect one or more target processes based on captured image data, each target process representing a sequence of user activities in the pre-defined environment, a blockchain unit configured to store the one or more target processes and a reference process in form of a private distributed logbook, wherein each of the target processes and the reference process include a series of process transactions, wherein each process transaction is stored in an encrypted form in the blockchain unit, and an analysis unit communicatively coupled to the blockchain unit, and configured to analyse the private distributed logbook by comparing each target process with the reference process to determine one or more anomalies therein.

Abstract: A risk exposure model is developed for network or moveable assets not specific to a single, fixed address or location. An asset map using a plurality of geographic representation points is used to identify the physical locations of the asset portions (or possible physical locations in the case of a moveable asset). Baseline geographic, geologic, political, and demographic data is similarly represented using geographic representation points. Meta-data associated with each geographic representation point is used to identify details related to the asset or baseline feature at that geographic location. Risk exposure values are then calculated using the geographic representation points specific to the asset portions that are subject to risks associated with the location of the asset portion.

Abstract: Systems, methods, and other embodiments associated with computing and generating schedule data structures for items in a display are described. In one embodiment, a method includes accessing a sales data structure corresponding to a store and analyzing sales records for items associated with subcategories to calculate a subcategory profit contribution score for each subcategory. The method may also include selecting a first subcategory from the subcategories as a candidate subcategory of items and analyzing the sales records to calculate an item profit contribution score for each of the items assigned to the candidate subcategory. A first item is selected from the candidate subcategory to be placed on a promotional display space, based upon the item profit contribution score of the first item. A schedule data structure is generated that assigns the first item to the promotional display space.

Abstract: Methods, apparatuses, non-transitory computer readable storage media, computer systems, networks, and/or systems for monitoring, collection, analysis, use and tracking of personal data, biometric data, medical data, transaction data, electronic payment data, location data and other data to develop a profile for one or more end user, pet, livestock, dairy cows, cattle or other animal using radio and other frequency tags and relaying data from EMFID tag interactions to a database that can be accessed by members of a network, and further including the use of unmanned surveillance vehicles, satellites or hand-held devices for monitoring, collection, and/or analysis of EMFID data.

Abstract: A data integration hub system includes a centralized database storing data according to a dimensional modeling schema. The data integration hub system accepts an external dataset from an external data source that stores data according to a database schema that differs from the dimensional modeling schema of the central database. The data integration hub translates the external data set into a first importable format compatible with the dimensional modeling schema of the centralized database, and imports the translated external dataset into the centralized database. The data integration hub also accepts online platform data from an online platform and imports the online platform data into the centralized database. In some cases, the data integration hub translated the online platform data prior to importation. The data integration hub generates client valuation profiles based on the data imported from the external data source and the online platform.

Abstract: The disclosed embodiments illustrate a method and a system for controlling KPI parameters of a transportation system. The method includes extracting historical commuting characteristics of one or more commuters, from a database server over a communication network. The method further includes generating a predictive model based on the extracted historical commuting characteristics. The method further includes generating a service schedule of one or more transportation services of the transportation system. The service schedule of the one or more transportation services may be generated by use of the generated predictive model, based on defined criteria of the transportation system. The method further includes controlling a KPI parameter of the transportation system to attain a desired KPI parameter of the KPI parameter, based on the generated service schedule, when the one or more transportation services are deployed at one or more time stamps.

Abstract: A device may communicate with a first server to obtain first information regarding a particular entity. The device may communicate with a second server to obtain second information regarding a plurality of entities. The device may process the first information and the second information to generate one or more recommendations for the particular entity. The one or more recommendations including a recommendation may relate to the particular entity altering an attribute of the particular entity to match an attribute of one or more of the plurality of entities. The attribute may be associated with a threshold level of performance for the one or more of the plurality of entities. The device may generate a user interface including the one or more recommendations. The device may communicate with a client device to cause the user interface to be provided for display.

Abstract: Systems and methods for allocating resources in a transportation system are disclosed. A vehicle of the transportation system may be dispatched by one or more processors; first and second portions of the vehicle are allocated to first and second groups of users. A parameter of the first group of users may be tracked at a first location. Part of the second portion of the vehicle may be reallocated to the first group of users, in real-time, when the tracked parameter of the first group of users exceeds a threshold.

Abstract: Systems and methods of dynamic optimization for data quality control in crowd sourcing tasks to crowd labor are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, for dynamically monitoring results received from workers for a task distributed for evaluation via a job distribution platform, incrementally assigning additional workers to the task using the results and continuously monitoring additional results to assign any additional workers if needed to meet a quality metric for the task.