MERCARI, INC.

Described herein are embodiments for improving search engine results of listings of For Sale Objects (FSOs). A search engine may be improved by implementing rules that resolve ambiguity between listings for different (FSOs) that match the same search inputs. An unsupervised machine learning module may evaluate candidate rules and identify improvements that may not be obvious to a human evaluator. An ecommerce site that combines the improved search engine with the unsupervised machine learning module may dynamically evaluate search results using different candidate rules and iteratively improve search results.

Embodiments described herein include modeling of seller profiles and behaviors on an e-commerce site to induce more listings and sales within the e-commerce site. For every seller and potential seller on the e-commerce site, their behaviors is to be understood and modeled in order to draw out more listings and completed sales per seller. An example embodiment of the present disclosure includes receiving a first information listing. At least one classification of the information listing may be generated performing at least one machine-learning (ML) process based at least in part on at least one ML model and the first information listing. A recommendation based on the classification of the first information listing may be generated. The recommendation may be recommending. A second information listing may be created.

Various embodiments for a transport dispatch system for marketplace curve sales transaction system are described herein. An embodiment operates by receiving, from a seller, an indication to sell a for sale item through an electronic marketplace. An item curve for the for sale item and a seller curve for the seller are generated. A sales curve is generated for the for sale item based on modifying the seller curve for the for sale item based on the item curve. A display of the sales curve is provided for the for sale item and an approval is received via a user interface. The electronic marketplace is monitored based on the approved sales curve, and the for sale item is sold for the seller based on a correspondence between the list price of the for sale item and a bid price.

Disclosed herein are system, computer-program product (non-transitory computer-readable medium), and method embodiments for machine-learning prediction or suggestion based on object identification. A system including at least one processor may be configured to cross-reference an identifier of a selected object with a list of known unique identifiers. The selected object may be selected via received selection. The at least one processor may further retrieve a set of values associated with the identifier of the selected object, upon determining that the list of known unique identifiers includes the identifier of the selected object, and perform machine-learning to derive a predicted-value set based at least in part on the set of values associated with the identifier of the selected object and a category applicable to the selected object. The at least one processor may determine that the predicted-value set satisfies a predetermined confidence condition, and output at least part of the predicted-value set.

A sensor includes: a sensor section including a conductive structure made up of a three-dimensionally continuous unit lattices, each including a plurality of columnar beams; and output connectors that output a resistance value of the sensor section, the resistance value changing at least when the conductive structure is compressed by an external force. A method for manufacturing a sensor includes forming the sensor section by stacking using a 3D printer. The sensor and method for manufacturing the sensor enable the adjustment of the repulsive force against compression to an input member and thus appropriately setting the change in resistance value against external force according to the device, in which the sensor is to be incorporated and the mode of use.

Disclosed herein are system, computer-program product (non-transitory computer-readable medium), and method embodiments for machine-learning prediction or suggestion based on object identification. A system including at least one processor may be configured to cross-reference an identifier of a selected object with a list of known unique identifiers. The selected object may be selected via received selection. The at least one processor may further retrieve a set of values associated with the identifier of the selected object, upon determining that the list of known unique identifiers includes the identifier of the selected object, and perform machine-learning to derive a predicted-value set based at least in part on the set of values associated with the identifier of the selected object and a category applicable to the selected object. The at least one processor may determine that the predicted-value set satisfies a predetermined confidence condition, and output at least part of the predicted-value set.

Various embodiments for a transport dispatch system for marketplace curve sales transaction system are described herein. An embodiment operates by receiving, from a seller, an indication to sell a for sale item through an electronic marketplace. An item curve for the for sale item and a seller curve for the seller are generated. A sales curve is generated for the for sale item based on modifying the seller curve for the for sale item based on the item curve. A display of the sales curve is provided for the for sale item and an approval is received via a user interface. The electronic marketplace is monitored based on the approved sales curve, and the for sale item is sold for the seller based on a correspondence between the list price of the for sale item and a bid price.

Provided herein are system, apparatus, device, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for identifying second products in an inventory of a second ecommerce site that are at least similar to a first product currently being displayed to an user by a first ecommerce site, and displaying the second products for viewing and purchase by the user at the first ecommerce site.

Disclosed herein are system, method, and computer program product embodiments for providing inventory ingestion and pricing system. An embodiment operates by identifying an e-mail receipt identifying a purchased object. The e-mail receipt is parsed for the identification of the purchased object. From an electronic marketplace, a set of items similar to the purchased object is identified. A price for a subset of the identified set of similar items that have sold on the electronic marketplace is determined. A sale price for the purchased object is generated based on the determined prices for the subset of similar items. The generated price is provided responsive to the identification of the purchased object.

Disclosed herein are system, method, and computer program product embodiments for providing inventory ingestion and pricing system. An embodiment operates by determining an identification of a for sale object to be sold on an electronic marketplace. A set of items similar to the identification of the for sale object are identified from the marketplace. A price of each of at least a subset of the set of similar items that have sold through the electronic marketplace is determined. A sale price is generated for the for sale object based on the determined prices of the items of the subset. An image for one or more of the subset of items, is retrieved from the electronic marketplace. A market descriptor comprising the sale price and the retrieved one or more images is generated. The market descriptor for display is provided for display.