The first candidate determination means 15B is configured to determine, based on seller information 41B indicating a sale condition of a transaction target presented by each of sellers and buyer information 42B indicating a buy condition of the transaction target presented by each of buyers, first candidates C1x to be plural candidates for combinations of the sellers and the buyers establishing valid transactions of the transaction target. The second candidate selection means 16B is configured to select plural second candidates C2x to be displayed from the first candidates C1x based on similarity among the first candidates C1x.

Various implementations described herein may refer to a system and method for trading emissions units. In one implementation, a method may include receiving emissions attribute data from users for emissions objects, where a respective emissions object is associated with a respective emissions output. The method may also include receiving evidence data from the users for the emissions objects, where the respective device is configured to transmit the evidence data to a distributed ledger. The method may further include determining emissions output data for the emissions objects. The method may additionally include transmitting the emissions output data to the distributed ledger. The method may also include generating emissions units for the users based on the emissions output data. The method may further include providing an emissions market platform to the users for trading the emissions units.

Disclosed herein are system, method, and computer program product embodiments for pooling requirements, such as placing of multiple purchase orders, while preserving the privacy of the requirements provided by requesters placing the orders. The approach involves receiving first encrypted information comprising a first request from a first client and second encrypted information comprising a second request from a second client. An encrypted intersection result of the first request and the second request can then be calculated using the first encrypted information and the second encrypted information, in their encrypted form without the need to decrypt either.

A system and a method are provided for directly communicating merchandise requests with vendors. The system and method enable customers to directly communicate with desired vendors to submit merchandise order requests with the necessary product information for the vendor to clearly identify. The user account enters a part order request for a specific vendor account. Once the part order request has been submitted by the user account, the part order request is relayed from the user account to the specific vendor account. Then, the specific vendor account accepts or declines the part order. Afterwards, the user account accepts or declines an order quote for the part order request, if the part order request is accepted by the specific vendor account. Then, a financial transaction for the part order request is executed between the user account and the specific vendor account, if the order quote is accepted by the user account.

Embodiments of systems and methods for the aggregation, analysis, display and monetization of pricing data for commodities in general, and which may be particularly useful applied to vehicles are disclosed. Specifically, in certain embodiments, historical transaction data associated with a particular vehicle configuration may be obtained and processed to determine pricing data associated with the vehicle configuration. The historical transaction data or determined pricing data may then be presented in an intuitive manner.

Methods and apparatus are disclosed regarding an e-commerce system having social networking aspects. The e-commerce system leverages such social networking aspects to help promote the sale of products.

According to examples, a system for transacting of virtual assets and/or associated non-fungible tokens (NFT) utilizing artificial intelligence (AI) and machine learning (ML) techniques is described. The system may include a processor and a memory storing instructions. The processor, when executing the instructions, may cause the system to generate a virtual asset; generate a non-fungible token (NFT) associated with the virtual asset; and determine a contractual item to facilitate a transaction for the virtual asset and the non-fungible token (NFT). The processor, when executing the instructions, may then generate a badge associated with the non-fungible token (NFT); receive an appraisal associated with the virtual asset; generate a valuation for the virtual asset based on the appraisal; and facilitate the transaction for the virtual asset and the non-fungible token (NFT) based on the valuation.

According to examples, a system for transacting of assets and/or associated non-fungible tokens (NFT) utilizing artificial intelligence (AI) and machine learning (ML) techniques is described. The system may include a processor and a memory storing instructions. The processor, when executing the instructions, may cause the system to identify a candidate asset, generate a transaction asset based on the candidate asset and generate a non-fungible token (NFT) associated with the transaction asset. The processor, when executing the instructions, may then determine a contractual item to facilitate a transaction for the transaction asset and a non-fungible token (NFT) associated with the transaction asset, generate a badge associated with the non-fungible token (NFT) and facilitate a transaction for the transaction asset and the non-fungible token (NFT).

A method of utilizing an artificial intelligence, AI, having language recognition software allowing the AI to have humanistic characteristics while interacting with the seller of used vehicle. The AI identifies online vehicles for sale and downloads the seller's contact information. The AI then validates or deletes the seller's contact information. The AI then interacts with a multiplicity of valid sellers to gather additional information on the vehicle as well as make an offer to purchase the vehicle.

An automated vending system includes a physical item storage unit, and a plurality of land-based transportation mechanisms, or vehicles, arranged to store a predicted number and assortment of items to vend. A processing resource can communicate with the plurality of transportation vehicles, and is arranged to support a machine learning module. A plurality of data sources is arranged to provide data to the machine learning module to determine a plurality of respective actions for the plurality of transportation vehicles. The processing resource can communicate respective control instructions to the plurality of transportation vehicles. A selected transportation mechanism which receives the control instruction can operate in response to the control instruction in order to convey the item to a determined vending location.