Systems and methods for buying and selling virtual items through multiple online sales platforms are disclosed. Exemplary implementations may: effectuate publications of at least two sales listings; effectuate a presentation to a buying user that includes representations of the publications; receive indications of offers to purchase the particular virtual item; determine an accepted offer that is accepted; effectuate assignment of the ownership of the particular virtual item to the buying user account.

A system for searching one or more images of goods includes a shopping mall server connected to a plurality of user terminals and configured to provide the user terminals with similar goods images matching a plurality of input goods images transmitted from the user terminals as a search result for recommended goods; and an input image analyzer communicationally connected with the shopping mall server and configured to receive information on the plurality of input goods images from the shopping mall server, calculate feature vectors corresponding to the input goods images, and transmit the calculated feature vectors to the shopping mall server. The shopping mall server includes a first database storing goods images for respective goods held by the shopping mall server and feature vectors corresponding to the goods images and a second database storing information on the goods images transmitted from the user terminal.

The systems and methods disclosed herein can increase the speed and ease with which a user can discover compatible replacement parts for a specified model of a product by automatically determining when the user is interested in replacement parts. A replacement part system can conclude that a user is looking for replacement parts based on the user's search queries, the user's browsing behavior, or the user's prior purchases. By automatically deducing an intention to purchase a replacement part, the replacement part system can make it easier for a user to locate suitable replacement parts. In addition, the replacement part system can be configured to tailor listing set of replacement parts search results it provides to a user. The set of search results can be tailored based on a number of criteria to increase the speed with which the user finds a compatible replacement part.

Ordering and delivery of food ingredients and food service items is opaque and inefficient. A computer system for recommending substitute food products to food service providers is disclosed. The system contains a database of information about food products that is continuously updated. The database is updated by food service providers and vendors submitting information about food products and the system tags the items entered and sorts them into the database. The system then provides recommendations to food service providers of substitute food products by comparing a food service provider's order history with a query entered with items in the database. A method for increasing efficiency in delivery of food products by streamlining the ordering and delivery process is also disclosed. The streamlined system includes options for price as a function of delivery route and a central container location for food delivery to multiple food service providers within one geographic location.

Systems and methods disclosed herein provide a geo-targeted online reservation system that ensures authenticity of customer devices requesting reservations by generating reservations only if threshold authentication conditions are satisfied. For example, a computing device registered with a server system receives inputs for requesting a reservation of a limited release product and for configuring the product. To authenticate the computing device, the server device transmits an electronic message to the computing device requesting the computing device to respond. A response to the message is one threshold authentication condition for generating the reservation. Upon determining that one or more threshold authentication conditions are satisfied, the server device generates a reservation for the product.

Systems and methods for providing a recommendation are disclosed. A method includes: presenting a first question via a user interface; receiving a response to the first question via the user interface; determining a second question using the received response to the first question and a weighted collection of attributes corresponding to a plurality of items; presenting the determined second question via the user interface; receiving a response to the second question via the user interface; determining at least one recommended item from the plurality of items based on the response to the first question, the response to the second question, and the weighted collection of attributes corresponding to the plurality of items; and presenting the determined at least one recommended item via the user interface.

A content provider can provide content, such as advertisements or other promotional material, to a recipient. A distribution system of the content provider can receive a query and select one or more advertisements and a user interface for presenting the advertisements based on the query, information associated with the user, a set of queries received from the user, and/or other information. A model for selecting the user interface can be generated by serving available user interfaces randomly or pseudo-randomly and monitoring user interaction with the served user interfaces. The model can be updated during regular use based on the performance of the user interfaces.

A warning device (100) includes: a biometric information acquisition unit (112) that acquires biometric information included in a captured image captured by a predetermined imaging device; an authentication request unit (114) that causes an authentication device (200) that stores biometric information of a plurality of users to perform personal authentication for the acquired biometric information; an attribute information acquisition unit (115) that acquires attribute information of a user who has succeeded in the personal authentication in a case where the personal authentication has succeeded; a substance information acquisition unit (116) that acquires substance information included in a product selected by the user; a determination unit (117) that determines whether or not the substance information corresponds to the attribute information; and an output unit (118) that outputs warning information to a predetermined display terminal in a case where the substance information corresponds to the attribute information.

A system and associated methods for authenticating physical or digital objects are disclosed. In at least one embodiment, a plurality of authentication devices is initiated, with each of the authentication devices associated with a one of the objects and containing a unique authentication sequence algorithm used to generate a sequence of device sequence values stored on each said authentication device. Upon a user desiring to authenticate a given object via a user application on a user device, the authentication device provides a data set to an authentication server. If the authentication server locates the authentication device in an authentication table, and subsequently processes the data set successfully, the authentication server obtains from the authentication table a server sequence value associated with the authentication device. If the device sequence value is later in the sequence than the server sequence value, the authentication server transmits a success message to the user application.

Technologies for machine learning-based product classification and approval are described. In some embodiments, a product data record is received and analyzed by machine learning models. The data record includes at least a product description, a product category, and a source organization. A first trained machine learning model is applied to the product description. The first trained machine learning model generates a product type. A second machine learning model is applied to the data record. The second machine learning model produces a classification that includes a confidence score. A decision rule is applied to the classification and the product type. An approval status is generated for the data record.