Abstract: According to one embodiment, an additional training apparatus includes processing circuitry. The processing circuitry stores, in a memory, a plurality of pieces of existing training data in which existing data is input data and a classification of defects according to the existing data is output data, and cluster data representing clusters to which the respective pieces of existing training data belong. The processing circuitry extracts a plurality of pieces of first existing training data from the pieces of existing training data in accordance with a size of each of the clusters. The processing circuitry acquires a plurality of pieces of new training data in which new data is input data and a classification of defects according to the new data is output data.

Abstract: According to an embodiment, a teaching device includes: an acquisition unit configured to acquire first input data; an estimation unit configured to estimate a first estimation result from the first input data, using a machine learning model; a search unit configured to search for a second taught estimation result taught for second input data, the second taught estimation result being associated with at least one of the second input data similar to the first input data, and a second estimation result similar to the first estimation result and estimated from the second input data, using the machine learning model; and a selection unit configured to select one selection candidate among a plurality of selection candidates including the first estimation result and the second taught estimation result, as a correction target estimation result to be used for correction of the first estimation result.

Abstract: Systems, methods, apparatuses, and computer program products for cluster based local ML model training host selection in asynchronous federated learning model collection. A method may include transmitting local model parameters following training of a model of at least one network element to a network node to be used to cluster the at least one network element with one or more other network elements. The method may also include training, by one or more network elements selected from the cluster, an aggregated model using the local model parameters. The method may further include transmitting, by the one or more network elements selected from the cluster, updated local model parameters of the at least one network element as a result of the training to the network node.

Abstract: A purpose of the present invention is to improve precision when estimating the solution to a task expressed in a graph. A model generation device according to one embodiment of the present invention performs machine learning of an estimation module provided with a feature-incorporated network and an estimator. The feature-incorporated network is provided with a plurality of feature-incorporated layers. An encoder for each feature-incorporated layer is configured so as to incorporate the feature amount of the outflow edge and inflow edge of each vertex after reflecting the relationship with other vertices. Moreover, the encoder for each feature-incorporated layer is configured so as to derive the relative feature amount for each edge based on the feature amount for all of the edges inputted for a target vertex, without calculating the weighted sum of the features of the edges adjacent to each vertex.

Abstract: A function input means 91 accepts input of a reward function whose features are set to satisfy a Lipschitz continuity condition. An estimation means 92 estimates a trajectory that minimizes Wasserstein distance, which represents distance between probability distribution of a trajectory of an expert and probability distribution of a trajectory determined based on parameters of the reward function. An update means 93 updates the parameters of the reward function to maximize the Wasserstein distance based on the estimated trajectory.

Abstract: Certain aspects of the present disclosure provide techniques and apparatus for improved machine learning. Input data comprising a plurality of points in multidimensional space is accessed. An edge connecting a first point and a second point of the plurality of points is identified, and the edge is mapped to a defined axis in the multidimensional space by applying a group element to the edge. An intermediate feature is generated by processing the mapped edge using a neural network. An output feature is generated by applying an inverse of the group element to the intermediate feature, and an output inference is generated based at least in part on the output feature.

Abstract: Aspects of the disclosure relate to apparatuses, method steps, and systems for optimized Internet of Things (IoT) data processing for real-time decision support systems. The systems are used for real-time processing prioritization using a prioritization code and/or processing code. Edge devices may generate processing codes that are used in optimizing the data processing. For example, the system receives sensor data and preprocesses the sensor data with a simplified state estimation module to calculate a variance that is used to determine a processing code and/or a prioritization code.

Abstract: A computer-implemented method for multi-task structural learning in artificial neural network in which both the architecture and its parameters are learned simultaneously. The method utilizes two neural operators, namely, neuron creation and neuron removal, to aid in structural learning. The method creates excess neurons by starting from a disparate network for each task. Through the progress of training, corresponding task neurons in a layer pave the way for a specialized group neuron leading to a structural change. In the task learning phase of training, different neurons specialize in different tasks. In the interleaved structural learning phase, locally similar task neurons, before being removed, transfer their knowledge to a newly created group neuron. The training is completed with a final fine-tuning phase where only the multi-task loss is used.

Abstract: In a kernel learning apparatus, a data preprocessing circuitry preprocesses and represents each data example as a collection of feature representations that need to be interpreted. An explicit feature mapping circuit designs a kernel function with an explicit feature map to embed the feature representations of data into a nonlinear feature space and to produce the explicit feature map for the designed kernel function to train a predictive model. A convex problem formulating circuitry formulates a non-convex problem for training the predictive model into a convex optimization problem based on the explicit feature map. An optimal solution solving circuitry solves the convex optimization problem to obtain a globally optimal solution for training an interpretable predictive model.

Abstract: Embodiments detect data drift associated with machine learning (“ML”) models. Embodiments identify a first feature stored by a feature store, where the feature store includes an offline store and an online store. Embodiments determine one or more first trained ML models that are using the first feature. For each of the first trained ML models, embodiments invoke the first trained ML model using synthetic data or validation data, generate metrics to determine an accuracy of the first trained ML model and, when the accuracy is below a threshold, generate an alert notifying of a first data drift for the first trained ML model.

Abstract: Systems and methods for reducing network traffic associated with a service. In some aspects, the systems and methods provide for using a first machine learning model to process a data stream for a communication with a user and generate a confidence score regarding whether to assign a communication suppression flag to the user account. Based on the confidence score not exceeding a first threshold, a communication suppression flag is not assigned to the user account. Based on the confidence score being between first and second thresholds, at least a portion of the data stream is extracted based on temporal proximity to a time stamp of an intent of the user to not receive further communications. Using a second machine learning model, the extracted portion of the data stream is processed to generate a prediction regarding whether to assign a communication suppression flag to the user account.

Abstract: A system and a method for generating and displaying candidate itineraries for travel. In an embodiment, the system receives, from an application installed on a client device, a request to book travel between an origin location and a destination location. The request includes multiple parameters. Responsive to receiving the request, the system applies a subset of the parameters to a constrained function, and ranks the routes between the origin location and the destination location by applying the constrained function to a route graph. The system then determines a subset of the routes based on the ranking, and requests from external data providers travel route data on the subset of routes. The system then determines candidate itineraries between the origin location and the destination location, and generates for display on the client device the candidate itineraries.

Abstract: Systems and methods for assisting wheelchair passengers where wheelchair assistance personnel utilize passenger information, airline information, and flight status information to assist passengers requiring wheelchairs. The flight status information is periodically updated. The systems and methods increase productivity of the wheelchair assistance personnel, which in turn reduces costs. The systems and methods also reduce or eliminate passenger waiting times and delays for a wheelchair.

Abstract: Aspects concern a method for controlling a transport system comprising determining historical data of a multiplicity of transport trips performed by the transport system, training a neural network to perform an invertible mapping of transport trips to latent representations to fulfil, by the distribution of the latent representations of the multiplicity of transport trips, a predetermined fitting criterion with respect to a predetermined latent representation base distribution, sampling a multiplicity of latent representations from the base distribution, mapping each of the sampled latent representations to a respective transport trip by using the trained neural network to perform the inverse of the invertible mapping to generate a multiplicity of synthetic transport trips, determining a control scheme for the transport system using the multiplicity of synthetic transport trips and controlling the transport system using the determined control scheme.

Abstract: The system may include a secondary irrigation feature that determines a percent of overlap of each of a plurality of submodules in a first lift over each of a plurality of submodules in a second lift and adjusts at least one of leaching operations or a leaching model based on the total tonnage weighted average of metal in the second lift. The method may further comprise determining an acid gap based on a difference between total acid given and total acid consumption; and further adjusting at least one of the leaching operations or the leaching model based on the acid gap. The method may further comprise determining a percentage of compacted material based on the material that is compacted and irrigated divided by the material that is irrigated; and further adjusting at least one of the leaching operations or the leaching model based on the percentage of compacted material.

Abstract: A decentralized dynamic policy learning and implementation system automatically processes incoming report and generates real-time data based on pre-configured rules and uses a graph-based transformer to generate new policies. The generation of the new polices is based on new alerts or notifications indicating an error with existing policies. An intelligent auto-router detects new security issues and re-routes information to generate the new policy and initiate analysis via a digital twin based on decisioning data points. The digital twin system qualifies the new policy to determine effectiveness in overcoming the security issue. An extended reality environment automatically generates an extended reality environment to based on a graph node structure of the policy.

Abstract: An incident that requires a resolution responsive to an event detected in a managed information technology environment is triggered. An incident type is obtained for the incident, where the incident type is selected from a set that includes a rare type, a novel type, and a frequent type. Responsive to determining that the incident is of the rare type or the frequent type, a list of recommended responders to address the incident is generated using a machine-learning model. Responsive to determining that the incident is of the novel type, a list of recommended responders to address the incident is generated based on a seniority level of responders. A selection of one of the recommended responders is received. The one of the recommended responders is associated with the incident.

Abstract: A system and method to generate a first skill-mapped item based on a mapping of at least a portion of first data associated with a first instructional product to a first skill in an ontology. A second skill-mapped item is generated based on a mapping of at least a portion of second data associated with a second instructional product to the first skill in the ontology. Based on first performance data associated with the first instructional product, a first estimate of skill proficiency corresponding to the first skill-mapped item and the first instructional product is determined. Based on second performance data associated with the second instructional product, a second estimate of skill proficiency corresponding to the second skill-mapped item and the second instructional product is determined. Based on the first estimate of skill proficiency and the second estimate of skill proficiency, a combined estimate of skill proficiency relating to the first skill is generated.

Abstract: The plant operation assistance system includes a plant information acquisition unit for acquiring plant information, an operator information acquisition unit for acquiring operator information, a work information acquisition unit for acquiring work information, a plant status identification unit for identifying a plant status from the plant information, a handling priority determination unit for determining handling priority for a plurality of units, a scheduling unit for creating schedule candidates from the handling priority, an operator state identification unit for identifying the status of an operator from the operator information and the work information, a schedule evaluation unit for evaluating the schedule candidates from the state of the operator, and a schedule presentation unit for presenting a schedule in accordance with the schedule evaluation result.

Abstract: An online concierge system maintains a data store with discrete time intervals for fulfilling orders and information on shoppers categorized in a tree structure based on their characteristics. When an order is received from a user's client device, the system employs a machine learning model trained on historical data to estimate the number of available shoppers and their corresponding levels in the tree structure. The order is tagged based on the items it contains, and these tags are matched to the levels of capable shoppers. Shoppers are grouped and scored based on their levels, and a group with the minimum score and capability to fulfill the order is selected. A shopper from this group is then dispatched for order fulfillment, leading to a decrement in the estimated number of shoppers in the selected group. This approach optimizes the allocation of shoppers to orders, ensuring efficient and timely fulfillment.

Abstract: A project monitoring method facilitated by a software application wherein the present invention provides a unique method that allows multiple entities involved in a project to receive updates thereon and further facilitate an improved communication workflow. The present invention includes a software application wherein the software application is operable to provide project creation wherein plans, drawings or similar material is uploaded into the software for the project. A user will identify a location coordinate on the plans or drawings and be able to upload a captured image of that identified location coordinate from the actual jobsite or area of the plan. This captured image is made available to other entities involved in the project and the present invention further facilitates communication therebetween. The present invention further provides the ability to annotate the images or location coordinate and provide notification of updates to all entities assigned to the project.

Abstract: The technologies described herein are generally directed to managing interactions between disparate resource types to complete tasks in an organization. For example, a method described herein can include identifying a task for achieving a task result, with task resources combining to complete the task including, communication resources, worker resources, and computer hardware resources. The method can further include mapping interactions between ones of the task resources to the task result. Further, the method can include, based on analyzing the interactions, allocate, for another task, additional interactions between selected ones of the task resources.

Abstract: An interactive and collaborative, planning, designing and facilitating tool that connects users with organized information and relevant data, providers and facilitators to resolve technical issues in conceptualizing, designing and implementing a custom project.

Abstract: A method for increasing sustainability of buildings includes obtaining building operational data from a plurality of building management systems and providing scores for a plurality of potential sustainable infrastructure projects by scoring the potential sustainable infrastructure projects based on at least one of utility information, climate data, building characteristics, or the building operational data. The scores can be generated at least in part on the building operational data. The method also includes providing, via a graphical user interface, a ranking of the potential sustainable infrastructure projects based on the scores.

Abstract: A system, for example, a document management system implements an asynchronous work queue for processing work items. Examples of work items include sending an email with a link to a document, execution of a document by receiving a user signature, collaborative editing of a document, configuring a form based on a document for presenting to a user, and so on. The system stores metadata describing work items in an asynchronous work queue. The asynchronous work queue repeatedly receives work items and stores metadata describing the work items. The system creates a work item container including a set of work items stored in the asynchronous work queue that were received during a particular time interval. The system provides the work item container, for example, to a subscriber for execution of work items in the work item container. The system repeats the process for each subsequent time interval.

Abstract: A graphical user interface provides visualization of operation tasks for a well ordered in a sequence. The graphical user interface shows different types of timing for the operation tasks, such as planned timing, estimated timing, and actual timing for the operation tasks. Different types of timing are arranged in a hierarchy so that setting one type of timing for an operation task overrides another type of timing for the operation task. Changes to timing of an operation task are automatically propagated to other operation tasks.

Abstract: If a headcount of workers on the one service day, the workers having been specified for one cleaning-assigned area that is assigned to one cleaning-service provider, is insufficient for a headcount that is necessary for a cleaning service on the one service day and that has been determined for the one cleaning-assigned area, one or more surplus workers who belong to another cleaning-service provider (workers who can work on the one service day and to whom none of cleaning services has been assigned) are allotted to resolve a shortage of staff for cleaning work in the one cleaning-assigned area.

Abstract: Some embodiments provide a novel method for monitoring health of logical networks. For a logical network including multiple LFEs, a health analytics manager identifies a set of one or more metrics associated with each LFE in the logical network. The health analytics manager uses the set of metrics to compute a health score for the logical network. Then, the health analytics manager provides the health score in a report to provide an indication regarding the monitored health of the logical network. In some embodiments, at least one LFE is implemented by multiple PFEs, and the set of metrics includes metrics associated with each of the PFEs implementing the at least one LFE.

Abstract: The disclosure may include an exemplary method comprising receiving risk metric data from a plurality of data sources; determining if the risk metric data passes quality control requirements; factoring the risk metric data; weighting the risk metric data by multiplying the weights at a sub-metric level; standardizing the risk metric data by scaling each risk value in the risk metric data to a range of values for each advisor to obtain standardized risk values; prioritizing the risk metric data by assigning a metric weight to the standardized risk values; further prioritizing the risk metric data by assigning a category weight to the standardized risk values; aggregating the risk metric data for an advisor to create advisor risk metric data; scoring a risk associated with the advisor based on the advisor risk metric data; and transferring the advisor risk data to a dashboard.

Abstract: An endpoint coupled in a communicating relationship with an enterprise network may include a data recorder configured to store an event stream of data indicating events on the endpoint including types of changes to computing objects, a filter configured to locally process the event stream into a filtered event stream including a subset of types of changes to the computing objects, and a local security agent. The local security agent may be configured to transmit the filtered event stream to a threat management facility, respond to a filter adjustment from the threat management facility by adjusting the filter to modify the subset of types of changes included in the filtered event stream, and respond to a query from the threat management facility by retrieving data stored in the data recorder over a time window before the query and excluded from the filtered event stream.

Abstract: An event organizer organizes and implements a virtual event. In connection therewith, the event organizer defines a set of high value actions (HVAs) for the event. The nature of the HVAs will vary depending on the event organizer, type of event, the available attendee activities, and the identity of the participants and the activities that are available to them at the event. The high value actions are prioritized, and weights are then attached to these actions. Once the event begins, participants at the virtual event engage in event touch points, and each participant-touch point interaction is monitored and recorded by the back-end systems. Typically, a participant engages in a touch point by selecting a display tab directed to that feature and exposed to the user on his or her browser during the virtual event.

Abstract: A system and platform are provided that enables end-users to gain insight into group and individual practices. Those insights may be obtained for any desirable aspect of each practice and the collection of practices including, but not limited to, financial information, medical information, human resources information, and patient information. That information can be used by group management to identify best practices, and it can be used to advise individual practices on strengths to be reinforced and weaknesses to be addressed. That information may be conveyed to group management and individual practices in the form of dashboards customizable to the particular functions of specific users and their personas.

Abstract: A method for identifying valid change points includes plotting original timeseries data; plotting a scaled cumulative sum of deviance from a mean applied on the timeseries data for generating a cumulative sum (CUSUM) chart; applying a piecewise linear fit (PWLF) on the CUSUM chart for generating a PWLF segment chart; identifying potential change points on the PWLF segment chart; determining an angle formed at each of the potential change points; comparing the determined angle for each of the potential change points against a reference angle limit; when the determined angle is less than the reference angle limit, discarding a corresponding potential change point, and when the determined angle is greater than the reference angle limit, calculating a significance value for the corresponding potential change point; and identifying a valid change point based on the significance value.

Abstract: A system for and method of determining anticipated voyage costs are provided. The system and method utilize a plurality of voyage simulations to determine cost information for each simulation. The voyage simulations utilize a digital twin model of a vessel, anticipated routes for the vessel, and weather data associated with each route. The results of the simulations are used to generate statistical probability for anticipated costs for a voyage, thereby facilitating more accurate predictions of costs that can be used to assess voyage feasibility and profitability.

Abstract: Embodiments classify a product to a product category. Embodiments receive a textual description of the product and create an index of product categories. Embodiments use a plurality of classifiers to classify the textual description to one of the product categories, the classifiers including an index based classifier, an encyclopedia based classifier, a Bayes' rule based classifier, and an embeddings classifier.

Abstract: A system and method are disclosed including a digital hub and a cloud database. The digital hub encodes, as a virtual supply chain network, the structure, one or more objectives, and one or more states of a supply chain network and contextualizes data received from one or more supply chain entities and one or more external data sources with the virtual supply chain network. The digital hub further employs machine learning to extract insights from the contextualized data and monitors external data sources for an event that may impact the one or more objectives of the supply chain network. Responsive to identifying an event that may impact the one or more objectives, the digital hub automatically adjusts one or more of robotic warehouse systems, robotic inventory systems, automated guided vehicles, mobile racking units, automated robotic production machinery, and robotic devices.

Abstract: Methods and apparatus for determining a parcel position error based on a comparison of load data and configuration data are provided. Embodiments describe a number of methods of determining the parcel position error such as by determining a parcel path from the load data.

Abstract: A big data modeling and analyzing method and system for shipping users. The method is applied to a shipping date and cargo matching platform including a client side and a background system; the client side is used for managing information related to the shipping date or a cargo by users comprising a ship owner user and a cargo owner user; the background system is connected with the client side by a network and is used for matching shipping date information with cargo information and pushing the shipping date information and the cargo information.

Abstract: A method, computer system, and a computer program product for securing transportation of Items. In one embodiment, packaging particulars may be determined including packaging configuration and materials. At least a sensor may be embedded when packaging the Item. The sensor type and location may be selected by a processor. The Sensor(s) may be selected to monitor changes to the condition of the Item during the transportation. Sensor data may be monitored and any risk to the Item during the transportation may be mitigated. In one embodiment, when a risk has been determined, an alert may be provided such as to a person or an IoT enabled device to mitigate the risk.

Abstract: Methods and systems for medication delivery using unmanned aerial vehicles (UAVs) are provided. The methods and systems: determine a target destination for a regional payload consisting of one prescription drug item, by a server communicatively coupled to: (i) a distance UAV comprising a fixed-wing aircraft configured to travel point-to-point to a regional hub, and (ii) a plurality of local UAVs comprising rotary wing, multi-rotor aircrafts residing at the regional hub; transmit instructions to the distance UAV to fly to the regional hub with a distance payload including a plurality of regional payloads; transmit instructions to a local UAV, to: obtain the regional payload consisting of the one prescription drug item; transport the regional payload to the target destination; perform lateral movement and hover operations to access a delivery site of the target destination; and deliver the one prescription drug item by releasing the regional payload at the delivery site.

Abstract: A matching making carrier service system and method that enables users to connect and collaborate on carrier services is described. The system provides a platform for users to search for each other for goods transportation purposes, such that a requester user and a traveler user can agree upon a freelance carrier service. The system may be configured to provide means to verify each user to provide reliable security of transactions between users. The system may be configured to provide escrow services to hold payment in secured means, such that payment may be configured to reliably provided upon completion of tasks. The platform may be configured to provide a feedback and review system such that users can be rated and ranked for the services rendered. The system may be configured to provide security encryption to ensure reliable interaction between users.

Abstract: Systems and techniques may be used for real time monitoring of content of a package. An example technique may include receiving sensor data sent from a first wireless telecommunications transmitter of a sensor device inside a package in transit, located together with content in the package, identifying whether the sensor data indicates that the content in the package was subjected to a condition outside of a specified range and receiving a status request for the package sent from a second wireless telecommunications transmitter of a mobile device based on a scanned machine-readable code on or affixed via a label to an outside face of the package. In response to receiving the status request, the technique may include sending an indication for display on the mobile device.

Abstract: Technologies are generally described for preparation and drone based delivery of food items. In some examples, a delivery vehicle may be arranged for autonomous or semi-autonomous preparation of food items while the vehicle is en route to a delivery destination or parked at the delivery destination. Aerial and/or ground based drones, which may be stored in the vehicle, may be loaded with prepared food items and deliver their payloads to delivery locations. Preparation timing and other parameters for the food items, travel parameters for the delivery vehicle, and/or the delivery destination may be selected based on suitability of the delivery destination for launching/recovering the drones or delivery of the food items to the delivery locations. The drones may carry multiple payloads to multiple locations and may have environmentally controlled storage.

Abstract: Systems and methods for delivery of items to an unspecified location, such as a moving location, are described. The systems and methods utilize a location-finding device to identify a location of a location-disclosing device associated with ordered items, and notify the location-disclosing device when an automated delivery device is within a predetermined proximity in order to arrange a specific location for delivery of the ordered items.

Abstract: The present disclosure is related to object recognition and tracking using multi-camera driven machine vision. In one aspect, a method includes capturing, via a multi-camera system, a plurality of images of a user, each of the plurality of images representing the user from a unique angle; identifying, using the plurality of images, the user; detecting, throughout a facility, an item selected by the user; creating a visual model of the item to track movement of the item throughout the facility; determining, using the visual model, whether the item is selected for purchase; and detecting that the user is leaving the facility; and processing a transaction for the item when the item is selected for purchase and when the user has left the facility.

Abstract: A method including generating, by separate instances of a multi-threaded worker system, respective lists of zip codes that fulfillment nodes in a fulfillment network can deliver to via ground shipping within a first shipping time period, based at least in part on preliminary eligibility information and an evaluation of current factors. The method also can include transforming, with an aggregator system, the respective lists of zip codes to generate a mapping from each zip code in the respective lists of zip codes to a respective list of the fulfillment nodes that can deliver via ground shipping to each zip code within the first shipping time period. The method additionally can include receiving a request comprising an input zip code and an input shipping time period.

Abstract: Disclosed herein is a food delivery system tailored to a consumer's eating patterns, which determines priorities of delivery according to a consumer's meal time to set a delivery line when delivering dietary food to a consumer, and transfers dietary food to a deliverer of a neighboring sector in a case in which it is difficult to deliver dietary food in time.

Abstract: The current document is directed to a meta-level management system (“MMS”) that aggregates information and functionalities provided by multiple management systems and provides additional management functionalities and information. In one implementation, the MMS interfaces to external entities and users through an MMS application programming interface (“API”) implemented as a GraphQL™ interface. The MMS API, in turn, accesses microservices and stream/batch processing components through microservice and stream/batch-processing-component GraphQL interfaces. The MMS employs at least three different databases: (1) an inventory/configuration database; (2) a metrics database that stores metrics derived from time-series data obtained from the multiple management systems and from other information stored in the inventory/configuration database; and (3) an MMS database that stores business insights and other MMS-generated data. A central data bus is implemented by a KAFKA™ event-streaming system.

Abstract: In retail, macro space optimization is carried out at individual stores to allocate optimum space for each category. Each retailer has many stores and macro space optimization is experimented with different objectives such as expand space, reduce space and constant space of a store individually. Thus, the number of space recommendations analyzed at corporate level increases extremely high and making it difficult to bring key inferences out of these recommendations and creating challenges in implementation of results such as creation of planograms and floor plans. Embodiments of the present disclosure provide a method and system for identifying underlying patterns that reside in space recommendations across stores and creating drastically reduced number of floor plans and planograms in accordance with the identified set of patterns unlike large number of floor plans or planograms generated by state of the art space planning systems.

Abstract: The disclosed technology provides for implementing remediations to item listing data in an online retail environment. A method can include receiving, by a computing system from a data management system, a topic for a change in item listing data, retrieving, from a data store, at least one model trained to (i) identify changes in other item listing data, (ii) determine at least one suggested remediation to the changes to generate accurate item listing data, and (iii) determine at least one confidence metric indicating a likelihood that the at least one suggested remediation will result in generating the accurate item listing data, inputting the item listing data to the at least one model, receiving output from indicating at least one suggestion to remediate the item listing data, determining that the at least one suggestion satisfies auto-remediation criteria, and auto-remediating the item listing data with the at least one suggestion.