Abstract: A network computing system can coordinate on-demand transport serviced by transport providers operating throughout a transport service region. The transport providers can comprise a set of internal autonomous vehicles (AVs) and a set of third-party AVs. The system can receive a transport request from a requesting user of the transport service region, where the transport request indicates a pick-up location and a destination. The system can determine a subset of the transport providers to service the respective transport request, and executing a selection process among the subset of the transport providers to select a transport provider to service the transport request. The system may then transmit a transport assignment to the selected transport provider to cause the selected transport provider to service the transport request.

Abstract: Systems and methods for determining an optimal delivery location based on delivery address and delivery time are provided. An example method includes receiving an online order from a user application installed on a user device; generating a map comprising a dynamic display of a local service area polygon associated with the online order and transmitting the map to the user application; transmitting to the user application a request for a delivery address; upon receipt of the delivery address, querying the delivery address to determine whether the local service area polygon includes the delivery address; transmitting to the user application a request for a delivery time; upon receipt of the delivery time, automatically recommending an optimal delivery location and time within the local service area polygon based on the delivery address and delivery time; and executing a delivery of the online order based on the optimal delivery location and time.

Abstract: Systems and methods which provide for determining seller categorization information using various information available in and to a shipping management system and for applying the seller categorization information to the operation of the shipping management system to provide fulfillment management services tailored for the seller are described. A feature set optimization engine of embodiments may implement various rules for inferentially determining one or more categories/subcategories for sellers using information that is not directly seller industry or product category information but which is otherwise utilized and available for shipping management functionality of a shipping management system. The feature set optimization engine may intelligently apply the inferentially determined seller categorization information with respect to one or more features of the shipping management system using various rules to implement an appropriate fulfillment management feature set.

Abstract: Identifying potentially unfair practices in content and serving relevant advertisements is described. A total risk score associated with an online advertisement is determined by a computer system based on a first risk score and an issue risk score. The first risk score is based on online content associated with the online advertisement and the issue risk score is based on one or more risk attributes associated with the online advertisement. The total risk score is transmitted to a client computer, where the total risk score is displayed through a user interface in conjunction with the display of the online advertisement on the client computer.

Abstract: A computer-implemented system for job matching of candidates and vacancies, comprises: a candidate memory storing data of at least one candidate profile associated with a respective candidate and consisting of a plurality of different candidate categories, wherein each candidate category comprises candidate category data associated with the candidate; and a vacancy memory storing data of at least one vacancy profile associated with a respective vacancy and consisting of a plurality of different vacancy categories, wherein each vacancy category comprises vacancy category data associated with the vacancy. A matching module is configured to receive the at least one candidate profile, receive the at least one vacancy profile, determine at least one similarity score between the at least one candidate profile and the at least one vacancy profile, and determine a job matching result based on the at least one similarity score. An information module is configured to communicate the job matching result to a user.

Abstract: A system and method for quantifying impact of script error exceptions on performance of an online retail platform. A method includes selecting at least one performance metric for a webpage, wherein the selected performance metric has an impact due to at least one script error exception encountered on the webpage visited by a first user device; retrieving a normal value for each of the at least one selected performance metric for the webpage visited by a second user device; retrieving an abnormal value for each of the at least one selected performance metric for the webpage visited by the second user device; comparing the abnormal value to the normal value of a respective selected performance metric; and determining a performance impact score based on the comparison, wherein the performance impact score is indicative of a reduction in a performance metric of each of the least one selected performance metric.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of storing, for each respective customer of one or more customers, respective customer information in a customer database; predicting, using a machine learning lifetime value (LTV) update model, a respective LTV for each respective customer of the one or more customers; determining an online advertisement for each respective customer of the one or more customers using the respective LTV, as predicted, for each respective customer of the one or more customers; and coordinating displaying the online advertisement for at least a portion of the one or more customers. Other embodiments are disclosed herein.

Abstract: Systems, methods, and computer program products for maintaining a collection of ecosystem credit tokens based on modelled outcomes are provided. In various embodiments, an ecosystem attribute target profile for the collection of ecosystem credit tokens is accessed. The target profile comprises a set of ecosystem characteristics, quantities of one or more ecosystem characteristics, and permanence of one or more ecosystem characteristics. A set of ecosystem credit tokens is accessed, wherein each ecosystem credit token data record comprises one or more of: a validated and verified management event, a methodology, an ecosystem attribute, a boundary, an ecosystem impact, an ecosystem credit, and an ecosystem attribute quantification method. A current profile of the collection of ecosystem credit tokens is determined, wherein the profile comprises the set of ecosystem characteristics within the collection, quantities of ecosystem characteristics, and permanence of ecosystem characteristics.

Abstract: Methods and systems are disclosed configured to control the planting, application of pesticides, and harvesting of greenhouse crops, such as herbs. The greenhouse may include a variety of sensors, such as moisture sensors, ph sensors, and/or CO2 sensors. Unmanned vehicles may be utilized to capture crop images, and a learning engine may be used to determine the size of greenhouse crops. Such sensor data may be used to predict crop availability. A predication engine may be utilized to predict demand for greenhouse crops using current and historical orders for greenhouse crops. Greenhouse crop production instructions may be generated and transmitted to a greenhouse computer system to cause crops to be sown or harvested. Pallet loading instructions may be generated regarding the loading of specified quantities of crop packs on respective pallets for shipment to a destination.

Abstract: Systems and methods presented herein provide a server that receives a service request from a user device. The server matches the service request against one or more technician profiles. Then the server sends a message to a corresponding technician device to accept the service request and starts an acceptance timer. If the technician accepts, the server sends a control application to the user device for installation. The user can enter a PIN received from the server into the control application, which then shares control of the user device with the technician device. The technician device can cancel the service request during a grace period. Otherwise, the technician must complete the service request. The control application can notify the server whether the service request was completed, and the server can update a score in the technician profile accordingly.

Abstract: Methods and apparatus are disclosed regarding an e-commerce system that clusters customers based on demographic data and purchase history data for the customers. In some embodiments, the e-commerce system solves an Integer Program that accounts for the demographic data and purchase history data in order to identify a hyperplane that splits a selected cluster of customers.

Abstract: In order to provide a survey that reflects details of a communication session between two parties, content of an established communication session between the parties is monitored. One or more topics in the content of the communication session are identified. For example, a voice communication between a customer and a call center agent can be monitored to identify a specific topic, such as a discussion about car insurance. Based on the identified topic, a survey is generated by incorporating the topic into the survey. For example, the survey can include a question regarding the customer's car insurance of his four wheel drive SUV, which was discussed during the call. The survey is then presented to or sent to a party of the communication session.

Abstract: Aspects of the disclosure relate to intelligent bot performance tracking and analysis. A computing platform may receive a work queue of items to be processed using a bot. The computing platform may receive, in real-time with processing of the work queue using the bot, metadata associated with the work queue. Based on the metadata, the computing platform may assign, in real-time, a value metric associated with completion of each item in the work queue. Based on the assigned value metric, the computing platform may identify a robotic process automation cost associated with processing the work queue via the bot. The computing platform may compare, the robotic process automation cost to a cost to process the work queue via another operation, and determine a performance metric for the bot based on the comparison. The computing platform may dynamically generate and transmit, in real-time, an indication of the determined bot performance metric.

Abstract: Systems, methods, and computer program products for recommending farming practices based on modelled outcomes are provided. In various embodiments, field data comprising geospatial boundaries of one or more field are received. Management event data comprising one or more management events within the one or more fields is received. For each management event, a management event boundary defining geospatial boundaries is received, and one or more management zones is determined based on the management event boundaries. The determination of one or more management zones comprises sequentially intersecting a geospatial boundary. Each sequential intersection operation creating two branches, one with the intersection of the geometries and one with the difference.

Abstract: Aspects of the disclosure relate to using machine learning for resource planning. A computing platform may detect an occupancy modification event for a physical space. Based on detecting the occupancy modification event, the computing platform may send commands directing display of a data collection prompt to end user devices, which may prompt for work to be performed by users of the end user devices in the physical space during a first day. Using natural language processing, the computing platform may analyze user input information and other occupancy data to determine whether or not the users of the end user devices have permission to occupy the physical space during the first day. The computing platform may cause the end user devices to display a resource management interface indicating whether or not the users of the end user devices have valid permission to physically occupy the physical space during the first day.

Abstract: Technologies are described for determining route proposals for shipment of cargo using unique location identifiers (ULIs). For example, a pickup ULI and a delivery ULI can be received. The pickup ULI and the delivery ULI are in the ULI data structure format defined herein. A first geographic area representing a pickup leg can be determined for shipment of the cargo from the pickup ULI to a first transportation network location and a second geographic area representing a delivery leg can be determined for shipment of the cargo from a second transportation network location to the delivery ULI. The main leg of the shipment occurs between the first transportation network location and the second transportation network location and travels through one or more defined transportation networks. Route proposals can be generated for shipment of the cargo through the pickup leg, main leg, and/or delivery leg.

Abstract: A product obsolescence forecast system includes machine instructions stored in a non-transitory computer readable storage medium, the machine instructions. A processor executes the instructions to receive an identity of a first product and identities of one or more second products similar to the first product, each of the second products having gone obsolete; receive a determinant of obsolescence of one or more of the obsolete second products; generate one or more observations related to the first product by inputting each received determinant to a trained network; and generate a statistical analysis of the one or more observations to provide an expected value of an actual obsolescence date for the first product.

Abstract: A first feature is displayed within a first view of a user interface. A first selection of the first feature is configured to display a first set of identifiers corresponding to one or more tasks. A second feature is displayed within the first view of the user interface. A second selection of the second feature is configured to display a second set of identifiers corresponding to a set of workers. Each worker of the set of workers is associated with the one or more tasks and a first time that the one or more tasks are scheduled to be completed by. A set of status indicators are displayed. Each status indicator of the set of status indicators indicates whether the one or more tasks have been completed by the first time for the each worker of the set of workers based at least in part on the associating.

Abstract: An online concierge system generates a suggested picking sequence to reduce the amount of time for a shopper to fulfill an online order of items from a warehouse. The online concierge system determines an average amount of time to sequentially pick items between different aisle pairs for a warehouse based on timestamps from item fulfillment in historical orders. The system generates a distance graph including aisle nodes connected by edges representing the pairwise distance between aisles. The system solves a traveling salesperson problem to generate a ranked order of aisle nodes for each of the historical orders. The system generates a ranked global sequence of aisle nodes based on the plurality of ranked orders of aisle nodes. The system applies the ranked global sequence to new delivery orders to generate the suggested picking sequence for a shopper.

Abstract: A system includes a computing device configured to receive order data indicating an order placed by a customer on an e-commerce platform and route the order into a test group or a control group when the order data indicates that the order will be filled by a store participating in the comparison test. The computing device is further configured to apply test features to the order if the order was routed into the test group and apply control features to the order if the order was routed into the control group and determine recommended substitute items based on the test features or the control features. The recommended substitute items are intended to replace items ordered by the customer that are unavailable. The computing device is also configured to determine one or more performance metrics of the test group and the control group.