# US 11,907,981 B2 · Context based online garage offering > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,907,981 B2 - Document ID: US11907981B2 - Status: Granted - Kind: B2 - Application number: 17/236,212 - Filed: 2021-04-21 - Published: 2022-10-27 - Granted: 2024-02-20 - Earliest claimed: 2021-04-21 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Shikhar Kwatra; Raghuveer Prasad Nagar; Jeremy R. Fox; Mauro Marzorati - Web page: https://patentgrep.com/patent/US11907981B2 ## CPC - G06Q 30/0609: {Qualifying participants for shopping transactions (payment transaction verification G06Q20/401)} - G06Q 30/0611: {Request for offers or quotes} - G06Q 30/0627: {by specifying product or service characteristics, e.g. product dimensions} - G06Q 30/0641: {utilising user interfaces specially adapted for shopping} - G06Q 10/30: Administration of product recycling or disposal - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract Embodiments herein disclose computer-implemented methods, computer program products and computer systems for context based online garage offering. The computer-implemented method may include receiving listing data from the seller users corresponding to items offered for sale, wherein the one or more seller users and one or more buyer users are registered with a web-based exchange platform based on user registration data; determining a seller context for the items based on the user registration data and the listing data; receiving historical item data for the items; determining disposal costs versus carry costs for the items based on the historical item data; determine potential buyers based on the listing data and potential buyer activity of the buyers; determining a buyer context based on the user registration data and the potential buyer activity; generating offer data for the items; and presenting the offer data to the seller users via a computing device user interface. ## Claims ### Claim 1 A computer-implemented method for optimizing clustering and contextual sale of items within a web-based exchange platform, wherein the web-based exchange platform resides in a distributed network, the computer-implemented method comprising: registering, by one or more processors, two or more users with the web-based exchange platform; generating, by the one or more processor a user interface of the web-based exchange platform; creating, by the one or more processor, a profile for the two or more users using the user interface of the web-based exchange platform, wherein the profile corresponding to the two or more users designates the two or more users as a buyer user or a seller user on the web-based exchange platform; configuring, by the one or more processors, a seller context implementing a ruleset for achieving a goal defined by the at least one of the two or more users designated as the seller user, offering one or more items for sale on the web-based exchange platform, wherein the seller context is based on one or more explicit sale offer, social media activity of the seller user and IoT data of the seller user; configuring, by the one or more processors, a buying context implementing a ruleset for achieving a goal defined by the at least one of the two or more users designated as the buyer user, wherein the buying context includes time constraints and budget constraints and is based on one or more explicit counteroffer of the buying user, social media activity of the buying user and IoT data of the buying user; receiving, by a first virtual assistant that is executed by the one or more processors, an online search query from the seller user regarding whether the seller user should sell the one or more items; responding, by the first virtual assistant that is executed by the one or more processors, to the online search query from the seller user; receiving, by a second virtual assistant that is executed by the one or more processors, an online search query from the buyer user regarding whether the buyer user should keep certain items associated the one or more items; responding, by the second virtual assistant that is executed by the one or more processors, to the online search query from the buyer user; generating, by the one or more processor, clusters of potential buyers from among the two or more users registered with the web-based exchange platform designated with the profile corresponding to the buyer user, for one or more items for sale on the web-based exchange by the seller user using a user classification technique to evaluate a plurality of profiles of the potential buyers, matching the profiles of the potential buyers with subscription interests of the one or more items for sale on the web-based exchange platform, wherein the user classification technique is K-means clustering; and executing, by the one or more processor, a trial-and-error iterative process determining whether the buyer context of the buyer user selected from the cluster of potential buyers and the seller context conform, wherein conforming occurs upon the buyer ruleset and the seller ruleset being satisfied within a predetermined threshold, facilitating automatic acceptance of a buyer user's outstanding offer to purchase the one or more items for sale and advancing the contextual sale of items to processing of payment on the web-based exchange platform. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein registering the two or more users with the web-based exchange platform includes receiving, by the one or more processor, user registration data comprising seller registration data and buyer registration data corresponding to respective user demographic data, respective user profile data, and respective user location data. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein the web-based exchange platform is one of a social media web-based platform or an online advertisement website. ### Claim 4 (depends on 1) The computer-implemented method of claim 1, wherein offering the one or more items for sale on the web-based exchange platform includes receiving listing data from the seller user, the listing data comprising one or more of an item description, an item image, an item price, item social media activity, IoT item specific data calendar data, and item specific search data. ### Claim 5 (depends on 4) The computer-implemented method of claim 4, wherein the item description comprises one or more of a reason for the sale, a time to complete the sale, bundle items, transportation cost, and an upper limit for the sale. ### Claim 6 (depends on 5) The computer-implemented method of claim 5, wherein determining the seller context further comprises: processing, by the one or more processors, the item description to generate a first item context; and generating, by the one or more processors, the seller context based on the first item context and the item description. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein the buyer context is based on potential buyer activity comprising counteroffers made by the potential buyers and recent item search history of the potential buyers. ### Claim 8 A computer program product for optimizing clustering and contextual sale of items within a web-based exchange platform, wherein the web-based exchange platform resides in a distributed network, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising: program instructions to register two or more users with the web-based exchange platform; program instructions to generate a user interface of the web-based exchange platform; program instructions to create a profile for the two or more users using the user interface of the web-based exchange platform, wherein the profile corresponding to the two or more users designates the two or more users as a buyer user or a seller user on the web-based exchange platform; program instructions to configure a seller context implementing a ruleset for achieving a goal defined by the at least one of the two or more users designated as the seller user, offering one or more items for sale on the web-based exchange platform, wherein the seller context is based on one or more explicit sale offer, social media activity of the seller user and IoT data of the seller user; program instructions to configure a buying context implementing a ruleset for achieving a goal defined by the at least one of the two or more users designated as the buyer user, wherein the buying context includes time constraints and budget constraints and is based on one or more explicit counteroffer of the buying user, social media activity of the buying user and IoT data of the buying user; program instructions to receive, by a first virtual assistant, an online search query from the seller user regarding whether the seller user should sell the one or more items; program instructions to respond, by the first virtual assistant, to the online search query from the seller user; program instructions to receive, by a second virtual assistant, an online search query from the buyer user regarding whether the buyer user should keep certain items associated the one or more items; program instructions to respond, by the second virtual assistant, to the online search query from the buyer user; program instructions to generate clusters of potential buyers from among the two or more users registered with the web-based exchange platform designated with the profile corresponding to the buyer user, for one or more items for sale on the web-based exchange by the seller user using a user classification technique to evaluate a plurality of profiles of the potential buyers, matching the profiles of the potential buyers with subscription interests of the one or more items for sale on the web-based exchange platform, wherein the user classification technique is K-means clustering; and program instructions to execute a trial-and-error iterative process determining whether the buyer context of the buyer user selected from the cluster of potential buyers and the seller context conform, wherein conforming occurs upon the buyer ruleset and the seller ruleset being satisfied within a predetermined threshold, facilitating automatic acceptance of a buyer user's outstanding offer to purchase the one or more items for sale and advancing the contextual sale of items to processing of payment on the web-based exchange platform. ### Claim 9 (depends on 8) The computer program product of claim 8, wherein the program instructions to register the two or more users with the web-based exchange platform includes program instructions to receive user registration data comprising seller registration data and buyer registration data corresponding to respective user demographic data, respective user profile data, and respective user location data. ### Claim 10 (depends on 8) The computer program product of claim 8, wherein the web-based exchange platform is one of a social media web-based platform or an online advertisement website. ### Claim 11 (depends on 8) The computer program product of claim 8, wherein offering the one or more items for sale on the web-based exchange platform includes receiving listing data from the seller user, the listing data comprising one or more of an item description, an item image, an item price, item social media activity, IoT item specific data, calendar data, and item specific search data. ### Claim 12 (depends on 11) The computer program product of claim 11, wherein the item description comprises one or more of a reason for the sale, a time to complete the sale, bundle items, transportation cost, and an upper limit for the sale. ### Claim 13 (depends on 12) The computer program product of claim 12, wherein the program instructions to determine the seller context further comprises: program instructions to process the item description to generate a first item context; and program instructions to generate the seller context based on the first item context and the item description. ### Claim 14 (depends on 8) The computer program product of claim 8, wherein the buyer context is based on potential buyer activity comprising counteroffers made by the potential buyers and recent item search history of the potential buyers. ### Claim 15 A computer system for optimizing clustering and contextual sale of items within a web-based exchange platform, wherein the web-based exchange platform resides in a distributed network, the computer system comprising: one or more computer processors; one or more computer readable storage media; program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to register two or more users the web-based exchange platform; program instructions to generate a user interface of the web-based exchange platform; program instructions to create a profile for the two or more users using the user interface of the web-based exchange platform, wherein the profile corresponding to the two or more users designates the two or more users as a buyer user or a seller user on the web-based exchange platform; program instructions to configure a seller context implementing a ruleset for achieving a goal defined by the at least one of the two or more users designated as the seller user, offering one or more items for sale on the web-based exchange platform, wherein the seller context is based on one or more explicit sale offer, social media activity of the seller user and IoT data of the seller; program instructions to configure a buying context implementing a ruleset for achieving a goal defined by the at least one of the two or more users designated as the buyer user, wherein the buying context includes time constraints and budget constraints and is based on one or more explicit counteroffer of the buying user, social media activity of the buying user and IoT data of the buying user; program instructions to receive, by a first virtual assistant, an online search query from the seller user regarding whether the seller user should sell the one or more items; program instructions to respond, by the first virtual assistant, to the online search query from the seller user; program instructions to receive, by a second virtual assistant, an online search query from the buyer user regarding whether the buyer user should keep certain items associated the one or more items; program instructions to respond, by the second virtual assistant, to the online search query from the buyer user; program instructions to generate clusters of potential buyers from among the two or more users registered with the web-based exchange platform designated with the profile corresponding to the buyer user, for one or more items for sale on the web-based exchange by the seller user using a user classification technique to evaluate a plurality of profiles of the potential buyers, matching the profiles of the potential buyers with subscription interests of the one or more items for sale on the web-based exchange platform, wherein the user classification technique is K-means clustering; and program instructions to execute a trial-and-error iterative process determining whether the buyer context of the buyer user selected from the cluster of potential buyers and the seller context conform, wherein conforming occurs upon the buyer ruleset and the seller ruleset being satisfied within a predetermined threshold, facilitating automatic acceptance of a buyer user's outstanding offer to purchase the one or more items for sale and advancing the contextual sale of items to processing of payment on the web-based exchange platform. ### Claim 16 (depends on 15) The computer system of claim 15, wherein the program instructions to register the two or more users with the web-based exchange platform includes program instructions to receive user registration data comprising seller registration data and buyer registration data corresponding to respective user demographic data, respective user profile data, and respective user location data. ### Claim 17 (depends on 15) The computer system of claim 15, wherein offering the one or more items for sale on the web-based exchange platform includes receiving listing data from the seller user, the listing data comprising one or more of an item description, an item image, an item price, item social media activity, IoT item specific data, calendar data, and item specific search data. ### Claim 18 (depends on 17) The computer system of claim 17, wherein the item description comprises one or more of a reason for the sale, a time to complete the sale, bundle items, transportation cost, and an upper limit for the sale. ### Claim 19 (depends on 18) The computer system of claim 18, wherein the program instructions to determine the seller context further comprises: program instructions to process the item description to generate a first item context; and program instructions to generate the seller context based on the first item context and the item description. ### Claim 20 (depends on 15) The computer system of claim 15, wherein the buyer context is based on potential buyer activity comprising counteroffers made by the potential buyers and recent item search history of the potential buyers.