Data content delivery and validation in a computer environment may provide a file system in the computer environment, the file system subdivided into unique folder locations per content type, each of the unique folder locations representing a content type folder. The file system is monitored for changes to a content type folder. An occurrence of a manifest file in the content type folder may be detected, the occurrence of the manifest file ensuring that all files in a package of files associated with the manifest file have arrived. Content of the manifest file may be analyzed to check validity of the files. A content package registry may be queried to determine a base job for processing a given content type associated with the package of files, and the base job may be run to process the package of files.

Disclosed herein are various embodiments for estimating shipping costs of items purchased on an online market. An embodiment operates by detecting a sales transaction between a seller and a buyer for an item via an online marketplace. An item vector representing the item as created by a deep learning model based on a plurality of characteristics associated with the item is received. A set of proximate vectors to the item vector, each of the proximate vectors corresponding to a past listings where a past shipping cost from shipping a product in the past listing is known are identified. A weighted average is calculated from the past shipping cost of each of the past listings. A dimensional weight of the item is estimated based on the weight average, and a shipping cost for the item is estimated based on the estimated dimensional weight prior to providing the item to a carrier.

Systems and method are provided for coordinating remote control of an autonomous vehicle by a remote transportation system. In one embodiment, a method includes: receiving, by a processor of the remote transportation system, request data requesting intervention of control of the autonomous vehicle; selecting, by the processor, an operator from a plurality of available operators; selectively assigning, by the processor, the selected operator to a task associated with the intervention based on at least one of a skill level of the selected operator, a workload of the selected operator, and an economic element of the ride associated with the selected operator; and coordinating, by the processor, control of the autonomous vehicle based on the assigned operator.

Systems and methods are described for providing dynamic guidance to purchasers using a fulfillment system to fulfill an order. The example systems can be configured to receive a request associated with an order and comprising an item identifier and an item quantity. The systems can estimate a request weight based on the item quantity and the item weight. The systems can also evaluate a request based on historical data associated with previous orders associated with the item identifier. The systems can select a dynamic default value based on the foregoing information and provide the dynamic default value for display to assist the purchaser.

Implementations set forth herein relate to systems, methods, and apparatuses for operating applications that allow users to indicate their willingness to provide items and/or services to other users and/or a third party. When an item is indicated as available for requesting, and an item is thereafter requested by a requesting user, a server device can cause instances of an item transferring application to provide a corresponding indication to item transferring users within a certain context. Values can be submitted by item transferring users, based on their current context, in furtherance of providing services that facilitate transfer of an item from an item creating user to an item requesting user. Other values can be submitted by the item transferring users in furtherance of characterizing a task of transferring items from a third party entity, who may not be accessing an associated application, to an item requesting user.

Disclosed is a method of managing order information of an electronic apparatus, the method including obtaining an order request including information on or regarding an item and information on a supplier of the item, identifying a type of the supplier based on the information on the supplier, when the type of the supplier is a first type, generating, in response to the order request, first order information for supplying the item from the supplier to a first business operator related to the electronic apparatus, when the type of the supplier is a second type, generating, in response to the order request, second order information for supplying the item from the supplier to a second business operator and third order information for supplying the item from the second business operator to the first business operator, and providing at least part of the generated order information.

A computer-implemented method for anonymizing online transaction details may include performing a process to generate an identifier (ID) and reference address for a user, and receiving a request for transaction processing from an e-commerce server. The request may include first data including: information associated with a purchase of a product to be delivered to the user; the identifier; and the reference address. The method may further include: in response to the request, determining whether the ID and reference address are included in the request, and if so, obtaining the accurate address and shipping rate rules; applying, based on the first data and the accurate address, the shipping rate rules to determine accurate shipping rate cost information associated with delivering the product to the accurate address; performing an anonymizing process on the accurate information to obtain anonymous shipping rate information, and transmitting the anonymous shipping rate information to the e-commerce server.

Provided is a system to generate a machine learning model to provide a predicted cost associated with shipping a shipment of freight from an origin of the shipment of freight to a destination of the shipment of freight based on a training dataset and a predicted distance and to determine the predicted cost associated with shipping a specified shipment of freight from the origin of the specified shipment of freight to the destination of the specified shipment of freight using the machine learning model. The training dataset includes data associated with shipments of freight conducted during a first time interval and data associated with shipments of freight conducted during a second time interval. The first time interval is at least a year and the second time interval is shorter than the first time interval. A computer implemented method and computer program product are also provided.

Techniques for generating an item transmission portal are described herein. First information for a plurality of carriers may be maintained which includes a capacity for each carrier. Historical capacity requirements for geographic locations may be maintained. For each geographic location a forecast of future capacity requirements, for each week of a plurality of weeks, may be generated based on the historical capacity requirements. A plurality of documents may be generated for each geographic location based on the forecast and the first information. A value may be determined for each document based on a time and capacity commitment for each document, the historical capacity requirements, and the forecast. A user interface may be generated that includes the plurality of documents and corresponding determined values. The user interface may be updated to reflect acceptance of a specific document by a carrier in response to input received via the user interface.

Disclosed is a method and system for optimal product sourcing. For each combination of the products requested in an order, and for each fulfilling location, the value of multiple parameters is calculated. Ranking of each parameter is also used while calculating the values. The calculated values along with the combinations of products and the fulfilling locations are provided to an optimization engine, and an optimal sourcing option is received as an output.