# US RE49,211 E1 · Decentralized multi-channel discovery system through a plurality of data structures > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US RE49,211 E1 - Document ID: USRE49211E1 - Status: Granted - Kind: E1 - Application number: 17/324,854 - Filed: 2021-05-19 - Granted: 2022-09-13 - Earliest claimed: 2017-03-29 - Assignees: ZYX Integrated Technologies, Inc. - Applicants: ZYX Integrated Technologies, Inc. - Inventors: Dante Carmelo Cullari; Mark Gregory Valente - Web page: https://patentgrep.com/patent/USRE49211E1 ## CPC - H04L 63/20: {for managing network security; network security policies in general (filtering policies H04L63/0227)} - G06F 16/951: Indexing; Web crawling techniques - H04L 63/102: {Entity profiles} - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Described herein are technologies related to an implementation of a decentralized discovery system that utilizes a plurality of fuse-nodes to facilitate delivery of content specific data to a user. The plurality of fuse-nodes is a proprietary owned database (or modules) that include relationship links to another fuse-node (s), and/or a particular channel, media, and contents, which further include social network-friends and social network activities of the social network-friend, etc. ## Claims ### Claim 1 A method implemented on one or more computing devices to populate a database comprising: initially configuring a plurality of fuse-nodes by a customizer that receives input variables and arranges one or more of categories, rankings, updates as to collected data from fuse-nodes, wherein a fuse-node includes relationship links to particular channels, media, and content, and denote different arrays of relevance to a user, wherein the initially configuring includes: marking each of the plurality of fuse-nodes with a corresponding identifier; setting at least one user-selected input variable, or content source, for a proprietary social recommendation algorithm to receive from and filter data for each of the plurality of fuse-nodes, wherein the algorithm is directed to a discovery process that is a request to show content from a collection of sources that are organized by fuse node fuse-node; ranking the collected data; configuring a privacy setting of the plurality of fuse nodes fuse-nodes, wherein the privacy setting includes a different permission model for each of the plurality of fuse-nodes; and forming a user-selected trust filter; storing the collected data based upon the initial configuration of the plurality of fuse-nodes; receiving an access-request to a plurality of fuse-nodes; determining an access-authorization of the received access-request based on a configured privacy-setting privacy setting of the plurality of fuse-nodes, wherein the access-request is received from a social networking site, and determining access level authorization of a requesting user; selecting collected data of the plurality of fuse-nodes based on the determined access-authorization; and supplying and encrypting the selected collected data to the requesting user. ### Claim 2 (depends on 1) The method of claim 1, wherein each data structure fuse-node in the plurality of fuse-nodes is a proprietary owned database, wherein the fuse-nodes include links to other fuse-nodes, channels, media, and contents, which further include social network-friends and social network activities of the social network-friends. ### Claim 3 (depends on 1) The method of claim 1, wherein the algorithm uses the user-selected social trust filter that limits recommended data from a social networking site, which is selected from a group of social media sources. ### Claim 4 (depends on 1) The method of claim 1, wherein the ranking of the collected data includes an assignment of a corresponding weight value to a sub-node, a channel, or a content of each of the plurality of fuse-nodes. ### Claim 5 (depends on 1) The method of claim 1, wherein the algorithm dynamically updates ranking of the collected data based on a user-selected time period. ### Claim 6 (depends on 1) The method of claim 1, wherein the algorithm dynamically updating of updates the collected data based on a fulfilment of a condition. ### Claim 7 A computing device comprising: one or more processors; and memory accessed by the one or more processors, the memory further comprises: a fuse-node register configured to facilitate initial configuration of a plurality of fuse-nodes, wherein the initial configuration is by a customizer that receives input variables and arranges one or more of categories, rankings, updates as to collected data from fuse-nodes wherein a fuse-node includes relationship links to particular channels, media, and content, and denote different arrays of relevance to a user, wherein the computing device receives an access request to the plurality of fuse-nodes, wherein access request is received from a social networking site, determination is made as to the received access-request based on a configured privacy-setting privacy setting that includes a different permission model for each of the plurality of fuse-nodes and access level authorization of the user; selection is made as to collected data of the plurality of fuse-nodes based on the determined access-authorization, and supplying and encrypting the collected data to the user; and supplying the selected collected data to a requesting user; wherein the plurality of fuse-nodes is are created by a local dataset that stores collected data based upon the initial configuration of the plurality of fuse-nodes; and a fuse-node customizer configured to arrange the stored collected data, wherein the initial configuration comprise comprises: marking each of the plurality of fuse-nodes with a corresponding identifier; setting at least one user-selected input variable for a proprietary social recommendation algorithm to receive from and filter data for each of the plurality of fuse-nodes, wherein the algorithm is directed to a discovery process that is a request to show content from a collection of sources that are organized by fuse node fuse-node; and configuring the privacy setting of the plurality of fuse-nodes. ### Claim 8 (depends on 7) The computing device of claim 7, wherein each fuse-node in the plurality of fuse-nodes is a proprietary owned database that include links to other fuse-nodes, channels, media, and contents, which further include social network-friends and social network activities of the social network-friends. ### Claim 9 (depends on 7) The computing device of claim 7, wherein the initial configuration further comprises: ranking the collected data. ### Claim 10 (depends on 7) The computing device of claim 7, wherein the algorithm uses a user-selected social trust filter that limits recommended data from a social networking site, which is selected from a group of social media sources. ### Claim 11 (depends on 7) The computing device of claim 7 9, wherein the ranking of the collected data includes an assignment of a corresponding weight value to a channel and a content of each of the plurality of fuse-nodes. ### Claim 12 (depends on 7) The computing device of claim 7, wherein the fuse-node customizer is further configured to dynamically update ranking of the collected data based on a user-selected time period. ### Claim 13 (depends on 7) The computing device of claim 7, wherein the algorithm updates ranking of the collected data based on a fulfilment of a condition. ### Claim 14 A non-transitory computer readable medium that comprises program instructions that causes a computer to perform the method comprising: initially configuring a plurality of fuse-nodes by a customizer that receives input variables that arranges one or more of categories, rankings, updates as to collected data from fuse-nodes, wherein a fuse-node includes relationship links to particular channels, media, and content, and denote different arrays of relevance to a user; storing collected data based upon the initial configuration of the plurality of fuse-nodes; receiving an access-request access request to a plurality of fuse-nodes, wherein the access request is received from a social networking site; determining an access-authorization of the received access-request access request based on a configured privacy-setting privacy setting of the plurality of fuse-nodes, wherein the privacy-setting privacy setting includes a different permission model for each of the plurality of fuse-nodes, and determining access level authorization of a requesting user; selecting collected data of the plurality of fuse-nodes based on the determined access-authorization; and supplying and encrypting the selected collected data to the requesting user, wherein the fuse-nodes are created by: marking each of the plurality of fuse-nodes with a corresponding identifier; setting at least one user-selected input variable for a proprietary social recommendation algorithm to receive from and filter data for each of the plurality of fuse nodes fuse-nodes, wherein the algorithm is directed to a discovery process that is a request to show content from a collection of sources that are organized by fuse node fuse-node; and configuring the privacy setting of the plurality of fuse-nodes. ### Claim 15 (depends on 14) The non-transitory computer readable medium of claim 14, wherein each data structure fuse node in the plurality of fuse-nodes is a proprietary owned database that include links to other fuse-nodes, channels, media, and contents, which further include social network-friends and social network activities of the social network-friends. ### Claim 16 (depends on 14) The non-transitory computer readable medium of claim 14, wherein creating the plurality of fuse-nodes further comprises ranking the collected data. ### Claim 17 (depends on 15) The non-transitory computer readable medium of claim 15, wherein the algorithm uses a user-selected social trust filter that limits recommended data from a social networking site, which is selected from a group of social media sources.